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Compared with large enterprises, the development scale and organizational structure of small and medium-sized enterprises are insufficient, which brings certain limitations to the development of small and medium-sized enterprises in China. In order to promote the long-term development of small and medium-sized enterprises in the new era, it is necessary to require enterprise leaders to innovate marketing plans, strengthen risk management of enterprises, and enhance their strength in market competition. The market risk evaluation of small and medium sized enterprises (SMSEs) in the new era is a multiple-attribute decision-making (MADM). The IVIFSs are employed as the tool for portraying uncertain information during the market risk evaluation of SMSEs in the new era. In this paper, the interval-valued intuitionistic fuzzy (IVIF) Hamacher interactive power geometric (IVIFHIPG) technique is addressed based on IVIF Hamacher interactive weighted geometric (IVIFHIWG) technique and power geometric (PG) technique. Some properties of IVIFHIPG technique were addressed. Then, the IVIFHIPG technique is employed to manage MADM under IVIFSs. Finally, an example for market risk evaluation of SMSEs in the new era is employed to verify the IVIFHIPG technique. Thus, the main contributions of this paper are addressed: (1) the IVIFHIPG technique is addressed based on IVIFHIWG technique and PG technique; (2) the IVIFHIPG technique is came up with to manage the MADM under IVIFSs; (3) a numerical example for market risk evaluation of SMSEs in the new era has been came up with to show the IVIFHIPG technique; and (4) some comparative analysis is addressed to verify the I IVIFHIPG technique. [ABSTRACT FROM AUTHOR]

Under the influence of the coronavirus disease and other factors, agricultural product prices show non-stationary and non-linear characteristics, making it increasingly difficult to forecast accurately. This paper proposes an innovative combinatorial model for Chinese hog price forecasting. First, the price is decomposed using the Seasonal and Trend decomposition using the Loess (STL) model. Next, the decomposed data are trained with the Long Short-term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. Finally, the prepared data and the multivariate influence factors after Factor analysis are predicted using the gated recurrent neural network and attention mechanisms (AttGRU) to obtain the final prediction values. Compared with other models, the STL-FA-AttGRU model produced the lowest errors and achieved more accurate forecasts of hog prices. Therefore, the model proposed in this paper has the potential for other price forecasting, contributing to the development of precision and sustainable agriculture. [ABSTRACT FROM AUTHOR]

Digital technologies, such as big data, the Internet, and artificial intelligence, are rapidly advancing. Photovoltaic building materials enterprises (PBMEs) have been leveraging digital transformation to enhance their technological innovation capabilities and gain a competitive edge. In the global context of transitioning towards a low-carbon economy, the deep integration of digital technology offers a new solution for the green transformation of PBMEs. The synergy between green traction digitalization and digitalization enables green practices, making collaborative integration crucial for the far-reaching development of PBMEs. Within the framework of China's "double carbon" policy, domestic PBMEs are experiencing exponential growth, where digital green innovation (DGI) has become their primary objective. In this DGI context, selecting the right partners is the first step that significantly impacts the efficiency and effectiveness of DGI implementation. Therefore, the purpose of this study is to assist PBMEs in selecting high-quality partners, promoting the DGI process, enhancing technological innovation capabilities, and gaining a competitive advantage. To achieve this, the paper proposes constructing a theoretical framework for evaluating the DGI cooperation ability of PBMEs using the theory of ecological reciprocity. Based on this framework, an evaluation index system is established to assess the DGI cooperation ability of potential partners The interval intuitionistic fuzzy evaluation method, combined with a double combination weighting approach, is employed to evaluate the DGI ability of selected partners. Furthermore, by applying field theory, a dynamic selection model for strategic alliance partners is developed to aid PBMEs in selecting high-quality partners for DGI and facilitating the DGI process. The research findings indicate that: i) The evaluation standard framework for DGI cooperation ability of PBMEs encompasses "symbiosis," "mutualism," and "regeneration," along with the crucial environmental element of mutual trust. ii) The evaluation method based on double combination weighting effectively assesses the comprehensive DGI capabilities of selected PBME partners. The application of field theory enables scientific and effective dynamic partner selection for PBMEs through resource complementarity. iii) The proposed framework and partner selection model can be employed in real partner selection scenarios for PBMEs, allowing them to choose high-quality partners, enhance their DGI capabilities, and attain practical selection outcomes. This paper presents novel partner selection model that integrates decision rules and resource complementarity, enabling PBMEs to efficiently select DGI partners from a pool of potential candidates and improve their innovation efficiency. The utilization of the double combination weighting method and field theory in the partner selection paradigm of D extends the theoretical foundation, while the establishment of the DGI capability evaluation index system for PBME partners contributes to empirical applications. [ABSTRACT FROM AUTHOR]

The development of rural preschool education (RPE) is not only related to the healthy growth of rural preschool children, but also to social fairness and sustainable development. Therefore, the development of RPE not only involves the expansion of quantity, but also the improvement of its quality. At present, in China's RPE, the determination of value goals There are still many obstacles in terms of source supply, institutional mechanism construction, development mode selection, and external environment construction, which make the high-quality development of RPE lack good internal motivation and external support. In view of this situation, some researchers have begun to explore the high-quality and sustainable development of RPE differently. However, the high-quality development of RPE is a systematic reform project that needs to start from the present. From multiple perspectives such as reality and history, internal and external education, this paper examines the systematic and global nature of RPE reform and development. The development level evaluation of RPE is a MADM. In this paper, the generalized weighted Bonferroni mean (GWBM) decision operator and power average (PA) is designed to manage the MADM under single-valued neutrosophic sets (SVNSs). Then, the generalized single-valued neutrosophic number power WBM (GSVNNPWBM) decision operator is constructed and the MADM model are constructed based on GSVNNPWBM decision operator. Finally, a decision example for development level evaluation of RPE and some useful comparative studies were constructed to verify the GSVNNPWBM decision operator. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence technology, the assessment method based on machine learning, especially the ensemble learning method, has attracted more and more attention in the field of credit assessment. However, most of the ensemble assessment models are complex in structure and costly in time for parameter tuning, few of them break through the limitations of lightweight, universal and efficient. This paper present a new ensemble model for personal credit assessment. First, considering the conflicts and differences among multiple sources of information, a new method is proposed to correct the category prior information by using the difference measure. Then, the revised prior information is fused with the current sample information with the help of Bayesian data fusion theory. The model can integrate the advantages of multiple benchmark classifiers to reduce the interference of uncertain information. To verify the effectiveness of the proposed model, several typical ensemble classification models are selected and empirically studied using real customer credit data from a commercial bank in China, and the results show that among various assessment criteria: the proposed model not only effectively improves the multi-class classification performance, but also outperforms other advanced multi-class classification credit assessment models in terms of parameter tuning and generalizability. This paper supports commercial banks and other financial institutions examination and approval work. [ABSTRACT FROM AUTHOR]

A consistency fuzzy set is composed of mean values and consistency degrees of fuzzy sequences in the transformation process of a fuzzy multiset (FM), but lacks confidence intervals in relation to a confidence level of fuzzy sequences, which shows its deficiency. To solve this deficiency, this paper aims to propose an improved transformation approach from FM to a confidence consistency fuzzy cubic set (CCFCS) and to develop an exponential similarity measure of CCFCSs for modeling piano performance evaluation (PPE) in a FM scenario. Consequently, this study includes the following context. First, a transformation approach from FM to CCFCS is proposed in terms of mean values, consistency degrees (the complement of standard deviation), and confidence intervals of fuzzy sequences subject to a confidence level and normal distribution. Second, the exponential similarity measure of CCFCSs is proposed in the scenario of FMs. Third, a PPE model is developed based on the proposed similarity measure of CCFCSs in the FM scenario. Finally, the developed model is applied to a piano performance competition organized by Shaoxing University in China as an actual evaluation example, and then the rationality and validity of the proposed model in the scenario of FMs are verified through sensitivity and comparison analysis. [ABSTRACT FROM AUTHOR]

The energy consumption of mechanical products in China is enormous, and the energy utilization rate is low, which is increasingly receiving people's attention. Conducting product design for energy optimization is of great significance for improving energy utilization efficiency. The scheme design of a product is the key to achieving innovation in product design, and the evaluation and decision-making of the design scheme directly affect the results of the later stage of the design. Therefore, correctly evaluating and making reliable decisions on product design schemes that are oriented towards fuzzy decision optimization is an important aspect of product innovation conceptual design. The product modeling design quality evaluation is a multiple attribute group decision making (MAGDM) problems. Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method has been employed to cope with MAGDM issues. The interval neutrosophic sets (INSs) are employed as a tool for portraying uncertain information during the product modeling design quality evaluation. In this paper, the CoCoSo method is designed for MAGDM under INSs. Then, the interval neutrosophic numbers CoCoSo (INN-CoCoSo) method based on the Hamming distance and Euclidean distance is built for MAGDM. The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs. Finally, a practical numerical example for product modeling design quality evaluation is supplied to show the INN-CoCoSo method. The main contributions of this paper are constructed: (1) This paper builds the novel MAGDM based on CoCoSo model under INSs; (2) The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs; (3) The new MAGDM method is proposed for product modeling design quality evaluation based on INN-CoCoSo. [ABSTRACT FROM AUTHOR]

As China's economic and social development enters a new stage, the role of innovation and entrepreneurship is becoming increasingly prominent, and its importance is also being emphasized. As the main force for future employment and national economic construction, college students naturally become the new force for innovation and entrepreneurship. Therefore, it is imperative for universities to carry out in-depth innovation and entrepreneurship education (IEE) for college students. Then, with the continuous development of social development needs and the professional growth needs of college students, the "innovation and entrepreneurship" education for college students should also be adjusted in a timely manner in terms of educational concepts, models, and methods. The IEE environment evaluation in universities under the background of " Double Innovation" is looked as multiple attribute decision-making (MADM). In this paper, the information entropy model is employed to calculate the objective weight of the evaluation attribute. Then, interval-valued intuitionistic fuzzy Combined Compromise Solution (IVIF-CoCoSo) is built based on the Hamming distance and Euclid distance to cope with MADM under interval-valued intuitionistic fuzzy sets (IVIFSs). The new MADM method is proposed for IEE environment evaluation in universities under the background of " Double Innovation". Finally, the IVIF-CoCoSo approach is compared with existing methods to verify the effectiveness of IVIF-CoCoSo algorithm. The main contributions of this constructed paper are: (1) the IVIF-CoCoSo method is built based on the Hamming distance and Euclid distance. (2) the information entropy model is employed to calculate the objective weight of the evaluation attribute. (3) The new MADM method is proposed for IEE environment evaluation in universities under the background of " Double Innovation" based on IVIF-CoCoSo. (4) The IVIF-CoCoSo model is compared with existing methods to verify the effectiveness of the IVIF-CoCoSo algorithm. [ABSTRACT FROM AUTHOR]

With the deepening reform of the medical and health system, China's community health services are also continuously improving. As the "gatekeeper" of community residents' health, community medical and health services provide basic health protection for community residents. In the final analysis, community medical and health service is a kind of service. In today's era where everyone pursues experience, improving service experience has become an important goal of modern health services. The community medical and health services evaluation is a multi-attribute group decision making (MAGDM) issue. The fuzzy number intuitionistic fuzzy sets (FNIFSs) are used as a tool for characterizing uncertain information during the community medical and health services evaluation. In this paper, a novel MAGDM is built on given CoCoSo method under FNIFSs for community medical and health services evaluation. First of all, this paper extends the CoCoSo to FNIFSs environment to build the fuzzy number intuitionistic fuzzy CoCoSo (FNIF-CoCoSo) method. Secondly, a new MAGDM model for community medical and health services evaluation based on CoCoSo algorithm is built. Finally, the practical example for community medical and health services evaluation to show the practicability and some comparisons are supplied to prove the effectiveness of the decision algorithm. [ABSTRACT FROM AUTHOR]

How to explore the potential value of landscape, realize the organic combination of tourism landscape, enrich landscape elements and enhance tourism experience has become an important topic of tourism landscape planning and design, which is also a practical problem that needs to be solved urgently in the process of tourism landscape development and planning in different regions of China. The tourism landscape planning design scheme evaluation based on the virtual reality technology a typical multi-attribute group decision-making (MAGDM) problem. With the complexity of economic activities, uncertain information has an increasing impact on production activities. However, due to the ambiguity and uncertainty of human cognition, the factors affecting the risk of things cannot be accurately expressed. Therefore, selecting spherical fuzzy sets (SFSs) can make the expression of information more accurate and complete. On basis of the TODIM method and the PROMETHEE method, in this study, spherical fuzzy number TOMIM-PROMETHEE (SFN-TOMIM-PROMETHEE) method is implemented to solve the MAGDM problem under SFSs. Furthermore, CRITIC method under SFSs is implemented to determine relative weights. Then a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology is selected to illustrate the effectiveness and practicality of the method. Finally, the comparative analysis shows that the SFN-TOMIM-PROMETHEE method under SFSs is an effective method to deal with MAGDM problems. The main contribution of this paper is managed: (1) the TODIM and PROMETHEE technique was extended to SFSs; (2) CRITIC technique is employed to manage the weight values under SFSs. (3) the SFN-TOMIM-PROMETHEE technique is founded to manage the MAGDM under IVPFSs; (4) a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology and comparison analysis are constructed to verify the feasibility and effectiveness of the SFN-TOMIM-PROMETHEE technique. [ABSTRACT FROM AUTHOR]

In the new normal period, the trend changes and adjustments of the environment such as international trade, production capacity, labor supply and resource constraints have put forward new requirements for China's industrial development, which have brought new challenges and given new opportunities. In the new normal stage where economic growth continues to decline, industrial growth is still an important support for economic growth. The advancement of industrial technology is the main driving force for improving the total factor productivity of the industrial industry. Therefore, the most important thing to promote industrial growth is to upgrade the level of industrial technology. In response to the above-mentioned problems, this paper analyzed the relationship between industrial technology and industrial output in the new normal environment by using the BP neural network (BPNN) algorithm. The connection between the two has been found, which provided a clear direction for the functional adjustment of economic law. Experimental studies have shown that there is a positive relationship between industrial technological progress and industrial output. When other conditions are the same, and when the non-new normal is selected, industrial output increases by about 0.36% for every 1% increase in industrial technological progress. When choosing to be in the new normal, industrial technological progress has a higher impact on industrial output. For every 1% increase in technological progress, industrial output increases by about 0.39%. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization and the significant improvement of people's living standards, the motorization of urban transportation in China has developed rapidly, and the number of urban motor vehicles has sharply increased. This has also caused a series of problems such as increasingly severe urban road traffic congestion, increased traffic energy consumption, and atmospheric environmental pollution. Unprecedented social and environmental pressures have put forward higher requirements for the development model of urban transportation. Against the backdrop of increasingly severe conflicts between urban transportation and resource environment in China, green transportation with the goal of "meeting maximum demand with minimum consumption" has gradually received widespread attention from the academic community. The urban green transportation development level evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy sets (TPFSs) and investigate the MADM problems under TPFSs. Based on the traditional geometric BM (GBM) operator and generalized weighted GBM (GWGBM) operator, some triangular Pythagorean fuzzy operators are proposed: triangular Pythagorean fuzzy generalized GBM (TPFGGBM) operator and triangular Pythagorean fuzzy generalized WGBM (TPFGWGBM) operator. Accordingly, we have took advantage of these operators to develop some approaches to work out the triangular Pythagorean fuzzy MADM. Ultimately, a practical example for urban green transportation development level evaluation is took advantage of to validate the developed approach, and an influence analysis of the parameter on the final results is been presented to attest its availability and validity. [ABSTRACT FROM AUTHOR]

China has now embraced the information era, which has had a significant impact on everyday life, employment, and educational practices. Information technology has also had a significant impact on the growth of the education sector, resulting in a fast-paced and resource-rich setting for student interaction. Through the network platform, various interactive software can improve students' learning methods, especially language teaching software. English audio-visual speaking is software for training English language listening and speaking, which can carry out relevant oral activities and topic discussions according to the imported materials. As a result, you can assist pupils in using the vocabulary and knowledge associated with the subject, which will increase their interest in learning. English teachers can fully prepare for speaking and listening tasks in the classroom by using audio-visual speaking. At the same time, through the learning of TV and movie trailers, English audio-visual speaking can provide readers with background knowledge, which is ready for readers to fully understand the language and content in the video materials. Based on information technology, this paper constructs English audio-visual and oral mobile teaching software, which depends on interactive digital media algorithms. Through the mobile teaching software for English audio-visual speaking, students can form good English listening and reading habits, which will provide important help for English language learning.First, this essay examines the value and benefits of mobile applications for providing English instruction orally and visually, which might help to illustrate the need for software development. The research then suggests various algorithms for English that are related to audio, visual, and oral input that can detect, assess, and correct students' learning mistakes. Finally, this work develops the fundamental methodology of the audio-visual and verbal mobile software for instruction in English. [ABSTRACT FROM AUTHOR]

Universities are important talent training bases in China and the main driving force for achieving the strategic layout of "revitalizing the country through science and education" and "strengthening the country through talent". Oil painting is a global art with rich humanistic and artistic value. Most art colleges in China have set up oil painting courses. Analyze the current situation and value of oil painting course teaching in local art (teacher training) majors, and leverage the educational role of oil painting courses by enriching course offerings, emphasizing the integration of humanistic innovation, improving teacher literacy, and striving to further improve the quality and efficiency of oil painting course teaching. The quality evaluation of oil painting teaching in universities is viewed as multiple-attribute decision-making (MADM). The grey relational analysis (GRA) is a useful tool to cope with the MADM issue. The probabilistic simplified Neutrosophic set (PSNSs) is easy to characterize uncertain information during the quality evaluation of oil painting teaching in universities. In this paper, in order to obtain the weight information, an optimization model implemented to obtain a simple and exact formula which can be employed to derive the attribute weights values based on the Lagrange function and the probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) technique is implemented for MADM to rank the alternatives. Finally, a numerical example for quality evaluation of oil painting teaching in universities is used to verify the practicability of the PSNN-GRA technique and compares it with other techniques. [ABSTRACT FROM AUTHOR]

Accurate prediction of the aging population can provide valuable reference and corresponding theoretical support for the adjustment of national population development policy and economic development strategy. To explore the future development trend of China's aging population, this paper establishes a novel fractional grey prediction model with the time power term (abbreviated as FGM (1, 1, t α) model) to study China's aging population. FGM (1, 1, t α) has the properties of fractional order accumulation operation and GM (1, 1, t α) model, which makes it good at capturing nonlinear features in time series. Furthermore, the quantum genetic algorithm is used to search for unknown parameters in the model to facilitate the solving task of the model. Data on China's aging population from 2000 to 2009 are used to train the prediction models, and data from 2010 to 2019 are used to evaluate the models' prediction performance. The results show that the FGM (1, 1, t α) model outperforms the other competing models, which means that it has good generalization. Finally, the FGM (1, 1, t α) model is used to forecast China's aging population from 2020 to 2029. [ABSTRACT FROM AUTHOR]

Optimizing the allocation of preschool education resources and improving the efficiency of resource allocation is of great strategic significance for the universal and inclusive development of preschool education and the realization of "education for young children". In recent years, the shift from high-speed development to high-quality development of the social economy has significantly improved the balanced development level of China's preschool education industry. However, preschool education remains the weakest link in China's education system and the most unfavorable aspect of educational resource allocation. Problems such as shortage of preschool education resources, insufficient investment, uneven regional development, imbalanced supply and demand structure, low resource allocation efficiency, and "difficult to enter, expensive to enter" are still prominent. How to optimize resource allocation and improve resource utilization efficiency in the limited resources of preschool education is the key to achieving balanced, fair, coordinated, and high-quality development of preschool education. The county preschool education resource allocation level evaluation is MAGDM problems. Recently, the TODIM and TOPSIS technique was employed to cope with MAGDM issues. The interval-valued Pythagorean fuzzy sets (IVPFSs) are employed as a tool for characterizing uncertain information during the county preschool education resource allocation level evaluation. In this manuscript, the interval-valued Pythagorean fuzzy TODIM-TOPSIS (IVPF-TODIM-TOPSIS) technique is built to solve the MAGDM under IVPFSs. Finally, a numerical case study for county preschool education resource allocation level evaluation is given to validate the proposed technique. The main contribution of this paper is managed: (1) the TODIM and TOPSIS technique was extended to IVPFSs; (2) Information Entropy is employed to manage the weight values under IVPFSs. (3) the IVPF-TODIM-TOPSIS technique is founded to manage the MAGDM under IVPFSs; (4) Algorithm analysis for county preschool education resource allocation level evaluation and comparison analysis are constructed based on one numerical example to verify the feasibility and effectiveness of the IVPF-TODIM-TOPSIS technique. [ABSTRACT FROM AUTHOR]

There is a lack of domestic and foreign research on the evaluation and improvement strategies of business performance of performing arts enterprises, especially in the context of the "restructuring" of cultural groups in China. Most of the existing studies are distributed in bulk, not only lacking in theoretical depth, but also lacking in systematization to a certain extent, which shows that the existing studies have not fully formed a mature and valuable theoretical system. The business performance evaluation of performing arts enterprises is a multiple attributes group decision making (MAGDM). This paper constructs a novel probabilistic hesitant fuzzy Multi-Objective Optimization Simple Ratio Analysis (PHF-MOOSRA) model based on the integrated determination of objective criteria weights (IDOCRIW) under the probabilistic hesitant fuzzy sets (PHFSs) for this issue. The PHFSs provides an evaluation circumstance containing more information which make the final decision-making results more accurately. Additionally, the IDOCRIW method separately and the MOOSRA method based on the MOORA method is proposed in PHFSs circumstance in this model. In the end, this model is then applied in a numerical case study for business performance evaluation of performing arts enterprises and compare this model with other existing methods. [ABSTRACT FROM AUTHOR]

After entering the 21st century, China's national economy has shown a rapid growth momentum, the comprehensive transportation system has been continuously improved, the road traffic infrastructure has made remarkable achievements, and the modern logistics industry has also risen rapidly and grown rapidly, which has greatly changed the market demand for road transport hubs. The road transport hub is the main node of the road transport network, the hub of passenger and freight distribution of road transport, and the organizational center for the interconnection of road transport and other transport modes and the development of comprehensive transport. Highway transportation hub is an important part of highway transportation infrastructure and plays an important role in highway transportation. The planning scheme evaluation of highway transportation hub is a multi-attribute decision making (MADM). This paper intends to propose a MADM methodology based on cross-entropy (CE) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for planning scheme evaluation of highway transportation hub. First of all, this paper extends the cross entropy method under the IVIFSs to propose the interval-valued intuitionistic fuzzy number CE(IVIFN-CE) method, it enlarges the application range of the CE method. Secondly, a new MADM model for planning scheme evaluation of highway transportation hub based on IVIFN-CE algorithm is proposed. [ABSTRACT FROM AUTHOR]

With the rapid development of China's construction industry, the competition in the construction industry is becoming increasingly fierce. Enterprises need to continuously improve their competitiveness in the market. Some non-core businesses can be outsourced to professional contractors. At present, contractors have more and more influence on the operation and development of enterprises. Whether it is the construction period or the quality of the project, it will have a greater impact on the operation of the construction project. In the environment of increasingly fierce market competition and increasing project quality requirements, for the construction project contracting enterprises, in order to achieve the goal of low cost and high quality, it is necessary to select the most suitable contractor on the basis of comprehensive consideration of multiple factors. The construction enterprise contractor selection is a classical multiple attribute group decision making (MAGDM) problem. In recent years, the MAGDM problem has become an important research field in modern decision science. This paper extends the EDAS method to the 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs). On the basis of the original EDAS method, 2-tuple linguistic Pythagorean fuzzy EDAS (2TLPF-EDAS) is built for MAGDM. Finally, a case study for construction enterprise contractor selection and some comparative analysis with the other methods show that the new method proposed in this paper is effective, reasonable and accurate. [ABSTRACT FROM AUTHOR]

The ocean plays a crucial role in human society's survival and development. While China's marine economy has grown rapidly in recent years, it has also led to serious problems inhibiting ecosystem sustainability. This paper proposes high-quality development of the marine economy and combines the improved entropy value method, fuzzy hierarchical analysis method (FAHP), and data envelopment analysis (DEA) method to establish a quadratic relative evaluation model. A two-layer comprehensive index framework with 19 indicators is built to measure various aspects of the marine economy, including innovation, coordination, green, openness, and sharing. Empirical analysis conducted on 11 coastal provinces in China using data mainly collected from the Chinese Statistical Yearbook reveals significant spatial patchiness in the high-quality development level of the marine economy. This discrepancy is largely due to differences in geographical locations, resources, and government policies. The study analyzes four benchmark provinces of high-quality development and summarizes their experiences. The paper concludes by providing suggestions and implications to support government decision-making. [ABSTRACT FROM AUTHOR]

In the 75th session of the United Nations General Assembly, the Chinese government first proposed the goal of carbon neutrality and carbon peaking. Since then, China's economy and society have undergone a comprehensive green and sustainable development upgrade and transformation. The development of green finance can provide financial support for achieving dual carbon goals and mitigate the impact of climate change. More importantly, it can contribute to the national economy's and society's sustainable development. We innovatively draw on the quality function deployment theory in marketing to logically formulate the research idea of this paper. On this basis, we also apply the G1-entropy method from fuzzy mathematical theory for quantitative research. We innovatively address the actual national conditions in China and fully integrate green elements in constructing the index system from green finance and sustainability perspectives. Finally, we calculate index weights through G1-entropy quantification to assess the development quality of China's green financial system and qualitatively propose countermeasures for the quality of China's green financial development with respect to key index factors. Specifically, we sort out this paper in the following three aspects: (1) we innovatively combined the quality function deployment theory and built the quantitative analysis process architecture in this paper, which enhanced the readability of this paper (2) we realized the use of quantitative research for qualitative analysis and proposed the G1-entropy value method, which made up for the defects of the subjective and objective methods in the traditional assessment methods (3) we realized the organic combination of quantitative and qualitative analysis and proposed relevant countermeasure suggestions based on the quantitative index calculation results, which provided relevant countermeasure suggestions for promoting the sustainable and high-quality development of green finance in China. Our study will provide a set of perfect assessment methods for the quality improvement path and sustainable development strategy formulation after the construction of China's future green financial system. It can also provide a reference assessment idea for the high-quality and sustainable development of China's green finance, which will further help China's economic transition to green and low-carbon and the achievement of the double carbon goal. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the coupling coordination degree of technology, economy, social responsibility, and ethic of technological innovation in high-tech enterprises, and provide basis for the optimization of technological innovation system structure in high-tech enterprises. Using data of high-tech enterprises in China Statistical Yearbook and China Statistical Yearbook of Science and Technology in 2018, the authors applied Cloud model to index transformation, consistent fuzzy preference relations to determine index weights, coupling degree model to measure the coupling degree of responsible innovation system of high-tech enterprises in China. Research results show that the responsible innovation system of China's high-tech enterprises in 2018 is in a low degree of coordination and coupling stage, and the high-tech enterprises in China invest relatively little in technical level, social development, and ethical innovation. This research contributes to the literature on responsible innovation, ethical responsibility in the high-tech enterprises, which is conducive to improving the quality of innovation activities. However, this research collected data from a single country at a single point in time. This paper studies from the perspective of responsible innovation and measures the coupling degree between innovation and ethical responsibility of high-tech enterprises. The establishment of coupling analysis model can not only effectively calculate the coupling degree of technological innovation system, but also deeply analyze the shortcomings of each subsystem of technological innovation system, and provide a basis for the formulation of promotion strategy. [ABSTRACT FROM AUTHOR]

With the proposal of the "Double First Class" construction concept in Chinese universities, cultivating high-quality talents has become the main direction of university education. At present, local universities in China are actively adapting to the changes of the times, taking the construction of the Double First Class as an opportunity, continuously adjusting and deepening the reform of the double innovation and innovation talent cultivation mode, further improving the curriculum system, increasing investment in professional practical teaching, stimulating students' enthusiasm for innovation and entrepreneurship (IAE), and focusing on improving students' comprehensive abilities, achieving significant results in talent cultivation. The "Entrepreneurship and Entrepreneurship" career ability evaluation of local college students could be considered as multiple attribute decision-making (MADM). Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method was employed to deal with MADM. The triangular fuzzy neutrosophic sets (TFNSs) are employed as a better tool for expressing uncertain information during the "Entrepreneurship and Entrepreneurship" career ability evaluation of local college students. In this paper, the triangular fuzzy neutrosophic number CoCoSo (TFNN-CoCoSo) based on the Hamming distance and Euclid distance is constructed to cope with the MADM under TFNSs. The information entropy method is employed to compute the weight values based on the Hamming distance and Euclid distance under TFNSs. Finally, a numerical example of "Entrepreneurship and Entrepreneurship" career ability evaluation of local college students is constructed and some decision comparisons are constructed to verify the TFNN-CoCoSo method. [ABSTRACT FROM AUTHOR]

China's education has entered the era of quality, and in order for higher vocational colleges to develop better, effective measures must be taken to improve the quality of education. Facing the continuous innovation of education in higher vocational colleges, it is necessary to strengthen institutional construction and constrain educational management with institutional constraints, which is the key to ensuring the education quality. The higher vocational education quality evaluation in the new era is regarded as multiple attribute decision-making (MADM). Recently, the EDAS and CRITIC model has been employed to solve MAGDM. The triangular fuzzy neutrosophic sets (TFNSs) are constructed as an efficient tool for portraying the uncertain information during the higher vocational education quality evaluation in the new era. In this paper, the triangular fuzzy neutrosophic number EDAS (TFNN-EDAS) model based on the Hamming distance and Euclid distance is constructed to solve the MADM under TFNSs. The CRITIC method is utilized to obtain the weight information based on the Hamming distance and Euclid distance under INNSs. Finally, a numerical example of higher vocational education quality evaluation in the new era is constructed and some efficient comparisons are founded to verify the TFNN-EDAS method. [ABSTRACT FROM AUTHOR]

Accurately predicting soybean futures fluctuations can benefit various market participants such as farmers, policymakers, and speculators. This paper presents a novel approach for predicting soybean futures price that involves adding sequence decomposition and feature expansion to an Long Short-Term Memory (LSTM) model with dual-stage attention. Sequence decomposition is based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method, a technique for extracting sequence patterns and eliminating noise. The technical indicators generated enrich the input features of the model. Dual-stage attention are finally employed to learn the spatio-temporal relationships between the input features and the target sequence. The research is founded on data related to soybean contract trading from the Dalian Commodity Exchange. The suggested method surpasses the comparison models and establishes a fresh benchmark for future price forecasting research in China's agricultural futures market. [ABSTRACT FROM AUTHOR]

With the continuous development of China's economic system, the development of the construction industry is becoming more and more rapid, and the number and scale of construction projects are increasing. Due to the characteristics of large projects and long cycles, there are a large number of construction parties involved in construction projects. The increase in the number of participating partners makes it difficult for their projects to be integrated and managed by management departments such as owners, let alone for various parties to collaborate in the construction of projects. In order to effectively solve this problem, the engineering procurement construction (EPC) general contracting model has emerged. The risk assessment of EPC project is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the risk assessment of EPC project. In this paper, the classical grey relational analysis (GRA) method is extended to PHFSs. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are introduced. Then, the definition of the score values is employed to obtain the attribute weights based on the information entropy. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for risk assessment of EPC project is designed to validate the proposed method and some comparative studies are also designed to verify the applicability. [ABSTRACT FROM AUTHOR]

At present, China's football sports are relatively backward in training theory and practice. If you want to break out of Asia and enter the world, and gain a firm foothold in the international football arena, you must use a scientific and realistic attitude, absorb the successful experience of advanced football countries, reflect on our training concepts and practices, and deeply study the training laws of football, in order to find a way suitable for our development. Athletes' competitive ability is the core issue of sports training. The failure of our football level is directly related to our systematic understanding of athletes' competitive ability. This problem has led to the separation of our training practice from the actual competition, making training unable to meet the needs of the competition. Only by solving this problem, can we improve the level of football in China. The football players' competitive ability evaluation is affirmed as multiple attribute decision making (MADM). In such paper, motivated by the idea of cotangent similarity measure (CSM), the CSMs are extended to DVNSs and four CSMs are created under DVNSs. Then, two weighted CSMs are built for MADM under DVNSs. Finally, a numerical example for Football players' competitive ability evaluation is affirmed and some comparative algorithms are produced to affirm the built method. [ABSTRACT FROM AUTHOR]

High-quality development of socio-economic, ecological environment, tourism industry and natural resources in the Yellow River Basin is a major strategic task for national development. High-quality development in the Yellow River Basin still has a lot of room for improvement, so it is important for the coupled and coordinated development of water resources-socio-economic-ecological environment-tourism industry in the Yellow River Basin region. In this study, we focus on the major strategic issues of high quality development in the Yellow River Basin in the context of the above-mentioned background and the current forms and policies of sustainable development in China, and conduct research on the theory and methods of assessing the sustainable development of regional water resources-socio-economic-ecological environment-tourism industry. However, by analyzing the existing research literature on sustainable development assessment, we find that most of them focus on a single area or two combinations of modal development studies, and focus on exploring micro-coupling mechanisms, so the generality of macro policy support is rather mediocre, which we fill this gap through this study. The study relies on an innovative macroscopic research perspective that draws pioneeringly on the quality function deployment (QFD) theory in the field of product quality management in marketing, which, it is worth stating, allows for a framework of research perspectives from a systematic and holistic perspective. In this framework, we will propose a G1-entropy value method for indicator importance (weight) assessment. It is worth stating that the G1 method used in this paper is different from the traditional G1 method in that we will introduce the identity information weights of experts to improve the reliability of the subjective assignment method. We will also construct an indicator system for studying the regional sustainable development issues in the Yellow River Basin on this basis, so as to complete the ranking and analysis of the nine provinces and the importance of indicators in the Yellow River Basin. This study will provide a comprehensive theoretical basis for Chinese government and related departments to formulate policies for the high-quality development of water resources, socio-economic, ecological environment and tourism industry in the Yellow River Basin, and also provide theoretical and empirical references for the analysis and assessment of similar international regional sustainability cases. [ABSTRACT FROM AUTHOR]

In this study, we focus on the analysis of factors influencing the siting decision of coal emergency reserve centers. Specifically, we first draw on the quality function deployment theory in marketing to logically integrate the ideas of this study. On this basis, we adopted an interdisciplinary fuzzy decision-making method, namely the G1-entropy method, to quantitatively evaluate the research of this paper. Thereafter, we constructed a three-level index system based on the characteristics of the coal emergency reserve site selection, and used the G1-entropy value method to calculate the weights of the indicators in the coal emergency reserve center siting decision index system and obtain the results. Our research findings have found that the three key indicators of coal conventional reserve, emergency coal transportation methods, and emergency response time play a crucial role in the decision-making of coal emergency reserve center location. Therefore, we propose specific countermeasures and suggestions for these three key indicators. Our study can provide support for the government to better select the location of emergency coal reserves, better improve the national energy layout, and provide support for relevant decision makers on how to better reserve coal. The location of the emergency coal reserve center can better play the role of strategic reserve to stabilize the market function, effectively respond to the impact of various events on the energy market, and can make corresponding suggestions to the construction of the national energy security reserve system. [ABSTRACT FROM AUTHOR]

The so-called wall hanging is actually a decorative picture hung indoors. It can also be said that painting, printing, dyeing, weaving, and embroidery on the fabric. The difference between traditional Chinese painting, watercolor painting, and oil painting lies in the fact that it is made in real objects with a material sense of texture, quality, and luster; Secondly, it has a purely decorative purpose; Therefore, it must be coordinated with the entire interior design. Judging from the current situation of production of wall hangings in China, most of them are high-end products such as wool weaving, flannelette embroidery, and embroidery, which are exclusively for export. The theme content is mostly taken from scenic spots and historical sites. The silk paintings unearthed in Mawangdui, Changsha, can also be regarded as the earliest wall hangings in China. Decorative wall hanging is an increasingly important item in modern interior decoration, and good decorative wall hanging is often regarded as the "finishing touch" in interior decoration design; It can refresh and brighten the indoor environment, and is an indispensable and important part of modern indoor overall design. The decorative wall hanging design effect evaluation is often considered as a multi-attribute decision making (MADM) problem. In this paper, the grey relational analysis (GRA) decision method is extended to the neutrosophic cubic sets (NCSs) setting to deal with MAGDM. First, the NCSs are reviewed. Then, the CRITIC is used to obtain the weights of attributes. In addition, the neutrosophic cubic number GRA (NCN-GRA) is established for MADM, and the computational steps for all designs are listed. Finally, the decorative wall hanging design effect evaluation is given to demonstrate the NCN-GRA model and some good comparative analysis is done to demonstrate the advantages of NCN-GRA. [ABSTRACT FROM AUTHOR]

With the continuous deepening of the construction of urban-rural economic integration in China, rural construction activities supported by rural revitalization strategies have changed the development thinking of rural economy. While implementing the goal of rural ecological economy, optimizing the rural living environment has become one of the important contents of rural revitalization, including the planning and design of rural landscapes. Rural landscape planning and design need to comprehensively consider the adaptability of landscape and rural ecological environment, emphasize the impact of rural spatial structure differences on landscape planning and design, and achieve scientific and humanized landscape planning and design, thereby creating a more warm, natural, and comfortable rural living space. The quality evaluation of tourism rural landscape planning and design is a multiple attribute group decision making (MAGDM) problems. Recently, the TODIM (an acronym in Portuguese of interactive and multicriteria decision making) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method has been inaugurated to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are inaugurated as a effective tool for characterizing uncertain information during the quality evaluation of tourism rural landscape planning and design. In this paper, the 2-tuple linguistic neutrosophic TODIM-VIKOR (2TLN-TODIM-VIKOR) method is inaugurated to solve the MAGDM under 2TLNSs. In the end, a numerical case study for quality evaluation of tourism rural landscape planning and design is inaugurated to confirm the proposed method. [ABSTRACT FROM AUTHOR]

How to guarantee the quality of college physical education (PE) teaching and reverse the declining trend of college students' physique year by year has become a hot topic for the research of higher education and school PE workers. The quality assurance of higher education in China should give full play to the role of colleges in teaching quality assurance activities, constantly improve the level of school running and improve the efficiency of school running. Because colleges themselves are the main body of higher education and teaching activities, they have the most power, qualification and responsibility to explain the quality of higher education. The classroom teaching quality (CTQ) evaluation of college badminton training is regarded as multi-attribute decision-making (MADM). The 2-tuple linguistic neutrosophic sets (2TLNSs) which the truth-membership, indeterminacy-membership and the falsity-membership are assessed by using the 2-tuple linguistic term sets is an appropriate form to express the indeterminate decision-making information in the classroom teaching quality (CTQ) evaluation of college badminton training. In this paper, the Hamy mean (HM) and the power average (PA) are connected with 2-tuple linguistic neutrosophic sets (2TLNSs) to propose the 2-tuple linguistic neutrosophic numbers weighted power HM (2TLNWPHM) operator. Then, use the 2TLNWPHM operator to handle MADM with 2TLNS. Finally, taking the CTQ evaluation of college badminton training as an example, the proposed method is explained. The main contributions of this study are summarized: the establishment of the 2TLNWPHM operator; (2) The 2TLNWPHM operator was developed to handle MADM with 2TLNS; (3) Through the empirical application of the CTQ evaluation of badminton training in universities, the proposed method is validated; (4) Some comparative studies have shown the rationality of the 2TLNWPHM operator. [ABSTRACT FROM AUTHOR]

The Dunhuang murals, notably the paintings on the interior walls of China's Dunhuang Grottoes, are considered international cultural treasure. The Dunhuang murals were ruined to varied degrees after a lengthy period of erosion. Deep learning networks were utilized to reconstruct broken parts of murals in order to better preserve their important historical and cultural values. Due to the presence of various damages, such as large peeling, mold and scratches, and multi-scale objects in the mural, a simple porting of existing working methods is suboptimal. In this paper, we propose a progressive Dunhuang murals inpainting (PDMI) based on recurrent feature reasoning network to progressively infer the pixel values of hole centers by a progressive approach, aiming to obtain visually reasonable and semantically consistent inpainted results. PDMI consists mainly of the FFC-based recurrent feature reasoning (RFR) module and Multi-scale Knowledge Consistent Attention (MKCA) module. The RFR module first fills in the feature value at the feature map's hole border, then utilizes the obtained feature value as a clue for further inference. The module steadily improved the limitation of hole centers, making the inpainted results more explicit; MKCA enables feature maps in RFR to handle richer background information from distant location information in a flexible manner while preventing misuse. After several round-robin inferences provide multiple feature maps, these feature maps are fused using an adaptive feature weighted fusion mechanism, then the fused feature maps decode back to RGB image. Experiments on a publicly available dataset and a self-made Dunhuang mural dataset reveal that the proposed method outperforms the comparison algorithm in both qualitative and quantitative aspects. [ABSTRACT FROM AUTHOR]

Gas gathering pipeline network system is an important process facility for gas field production, which is responsible for collecting, transporting and purifying natural gas produced by wells. In this paper, an optimization model for the layout of star-tree gas gathering pipeline network in discrete space is established to find the most economical design scheme. The decision variables include valve set position, station position and pipeline connection relation. A series of equality and inequality constraints are developed, including node flow balance constraints, pipeline hydraulic constraints and pipeline structure constraints. A global optimization strategy is proposed and an improved genetic algorithm is used to solve the model. To verify the validity of the proposed method, the optimization model is applied to a coalbed methane field gathering pipeline network in China. The results show that the global optimization scheme saves 1489.74×104 RMB (26.36%) in investment cost compared with the original scheme. In addition, the comparison between the global and hierarchical optimization scheme shows that the investment cost of the global optimization scheme is 567.22×104 RMB less than that of the hierarchical optimization scheme, which further proves the superiority of the global optimization method. Finally, the study of this paper can provide theoretical guidance for the design and planning of gas field gathering pipeline network. [ABSTRACT FROM AUTHOR]

Disputes are inevitable in construction. Tremendous losses caused by dispute are so amazing that professionals try to figure out how to manage it. It is a practical way to study the dispute problem from the perspective of governance theory. In this study, the paper intends to investigate the characteristics of contractual governance for disputes. Based on governance theory, the framework of contractual governance for dispute is constituted of governance structure (GS) and governance mechanism (GM). The flexibility of GS and GMs are all explored so as to better draft the contracts. By a multiple cases study, a new conceptual model instructing governance picture for construction disputes was proposed which was mainly inspired from literature. The cases study shows that the GS determination is rigidly drafted and executed while the mostly GMs are flexibly designed. The rigid GS has an advantage to a stable foundation and the flexible GMs are apt to coordinate the disputes. [ABSTRACT FROM AUTHOR]

Some subtle features of planting structures in irrigation areas could only be visible on high-resolution panchromatic spectral images. However, low spatial resolution multispectral image makes it hard to recognize them. It is challenging to accurately obtain crop planting structure when using traditional methods. This paper proposes an extraction method of crop planting structure based on image fusion and U-Net depth semantic segmentation network, which can automatically and accurately extract multi-category crop planting structure information. This method takes Landsat8 commercial multispectral satellite data set as an example, chooses RGB pseudo-color synthetic image which highlights vegetation characteristics, and uses HLS(Hue, Luminance, Saturation), NND(Nearest-Neighbor Diffusion) and G-S(Gram-Schmidt) methods to fuse panchromatic band to obtain 15m high-resolution fusion image to obtain training set and test set, six types of land features including cities and rivers were labeled by manual to obtain the verification set. The training and validation sets are cut and enhanced to train the U-Net semantic segmentation network. Taking the Xiaokaihe irrigation area in Binzhou City, Shandong Province, China, as an example, the planting structure was classified, and the overall accuracy was 87.7%, 91.2%, and 91.3%, respectively. The accuracy of crop planting structures (wheat, cotton, woodland) was 74.2%, 82.5%, 82.3%, and the Kappa coefficient was 0.832, 0.880, and 0.881, respectively. The results showed that the NND-UNet method was suitable for large-scale continuous crop types (wheat, cotton), and the GS-UNet method had a better classification effect in discrete areas of cash crops (Jujube and many kinds of fruit trees). [ABSTRACT FROM AUTHOR]

Tourism is the most culturally loaded industry. In the new era, China's tourism industry is developing rapidly and the public's need for diversified culture is growing. The integration of culture and tourism, the development of new forms of cultural tourism industry, is also an important means to enhance the country's cultural soft power, promote the development of China's tourism culture, and solve the contradiction between cultural supply and demand. The industrial competitiveness evaluation of regional cultural tourism is looked as the multiple attribute group decision-making (MAGDM) problem. This paper proposed extended MARCOS method in probabilistic hesitant fuzzy sets (PHFSs) circumstance. Meanwhile, the CRITIC method is used to evaluate the criterion weights. Then we give a case study for industrial competitiveness evaluation of regional cultural tourism to measure the novel model's validity. [ABSTRACT FROM AUTHOR]

Due to the increasingly strengthened role of finance in modern economic development, theoretical research on regional financial competitiveness in the study of regional economic competitiveness becomes very important. For China at this stage, finance is in a period of rapid development, and its role has penetrated into all aspects of social and economic life. Especially after China's entry into the WTO, the pace of opening up the financial market has been further accelerated, and comprehensive evaluation and analysis of financial competitiveness is of great significance for comprehensively understanding and accurately grasping China's national conditions, national strength, and international competitiveness, promoting the long-term growth of China's financial competitiveness, and the sustainable development of the financial industry. The competitiveness evaluation of regional financial centers is looked as the multiple attribute decision-making (MADM) problem. This paper intends to propose a MADM methodology based on CoCoSo (Combined Compromise Solution) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for sustainable competitiveness evaluation of regional financial centers. At the end of this study, we noticed to a comparison between the proposed IVIF-CoCoSo approach with other existing methods to verify the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Preference relations are often used to derive the priority of attributes and/or alternatives. Linguistic term with weakened hedges (LTWH) as a type of complex linguistic expressions can more straightforwardly describe the linguistic information provided by DMs when evaluating under uncertainties. The preference relations represented by LTWHs are an effective tool to model linguistic information. The concept and properties of additive consistency have been proposed before. This paper aims to study the multiplicative consistency of preference relations expressed by LWTHs. This paper constructs the principle of inspection for multiplicative consistency. Especially, the theories and algorithms for consistency checking and improving are proposed. We develop an automatic approach to improve a LWHPR that is not multiplicatively consistent. Finally, we demonstrate the practicality of the proposed method through a case study of evaluating the attributes in the prevention of haze pollution in China. [ABSTRACT FROM AUTHOR]

In this paper, 1,538 papers retrieved with the keywords "sports artificial intelligence (AI)" on the Web of Science database since 2007 were taken as the data source, and the Cite Space V software was used to visualize and analyze them. A visual knowledge graph was used to streamline the countries, institutions and authors conducting sports AI research, discipline distribution, research hotspots and development trends in the past 15 years. Subsequently, its development direction and research progress were discussed. Sports AI was widely distributed, with the US, China and the UK leading the way. The most prolific authors and teams in research on sports AI were concentrated in American universities. Their main research direction is to develop and improve smart wearable devices based on machine learning and deep learning technologies for different groups of people. Research on sports AI involved multiple disciplines, which mainly applied and referred to research methodologies and theories on engineering, computer science and sports science. It could be seen from the frequency and centrality of keywords that in the current field of sports AI, machine learning is the main direction, artificial neural networks is the main algorithm, and practical and empirical research based on data mining is the focus. The research hotspots were divided into three major clusters: physical health promotion, sports injury prevention and control, and athletic performance enhancement. How to introduce intelligent technology into sports for a perfect integration still has an arduous and long way to go. Future development requires joint efforts and participation of scientific researchers, professionals and common people. [ABSTRACT FROM AUTHOR]

An important feature of the outbreak of systemic financial risk is that the linkage and contagion of risk amongst the various sub-markets of the financial system have increased significantly. In addition, research on the prediction of systemic financial risk plays a significant role in the sustainable development of the financial market. Therefore, this paper takes China's financial market as its research object, considers the risks co-activity among major financial sub-markets, and constructs a financial composite indicator of systemic stress (CISS) for China, describing its financial systemic stress based on 12 basic indicators selected from the money market, bond market, stock market, and foreign exchange market. Furthermore, drawing on the decomposition and integration technology in the TEI@I complex system research methodology, this paper introduces advanced variational mode decomposition (VMD) technology and extreme learning machine (ELM) algorithms, constructing the VMD-DE-ELM hybrid model to predict the systemic risk of China's financial market. According to eRMSE, eMAE, and eMAPE, the prediction model's multistep-ahead forecasting effect is evaluated. The empirical results show that the China's financial CISS constructed in this paper can effectively identify all kinds of risk events in the sample range. The results of a robustness test show that the overall trend of China's financial CISS and its ability to identify risk events are not affected by parameter selection and have good robustness. In addition, compared with the benchmark model, the VMD-DE-ELM hybrid model constructed in this paper shows superior predictive ability for systemic financial risk. [ABSTRACT FROM AUTHOR]

Uncertain statistics is a set of mathematical techniques to collect, analyze and interpret data based on uncertainty theory. In addition, probability statistics is another set of mathematical techniques based on probability theory. In practice, when to use uncertain statistics and when to use probability statistics to model some quality depends on whether the distribution function of the quality is close enough to the actual frequency. If it is close enough, then probability statistics may be used. Otherwise, uncertain statistics is recommended. In order to illustrate it, this paper employs uncertain statistics, including uncertain time series analysis, uncertain regression analysis and uncertain differential equation, to model the birth rate in China, and explains the reason why uncertain statistics is used instead of probability statistics by analyzing the characteristics of the residual plot. In addition, uncertain hypothesis test is used to determine whether the estimated uncertain statistical models are appropriate. [ABSTRACT FROM AUTHOR]

As one of the teaching models that promote the orderly development of vocational education in China, the integration of industry and education has been recognized by all sectors of society in China's many years of practice. In recent years, with the strong advocacy of the education sector in China, its development speed has been rapidly improved. Rural vocational education in China has also actively implemented and innovated the teaching mode of integration of industry and education, which has trained more excellent talents for agricultural development in various regions. The quality evaluation of industry-education integration for rural vocational education in the perspective of rural revitalization is viewed as the multiple attribute group decision making (MAGDM). In this paper, the probabilistic linguistic Mixed Aggregation by Comprehensive Normalization Technique (PL-MACONT) method is built for MAGDM. At last, to verify the validity of the extended method, a numerical example to further account for quality evaluation of industry-education integration for rural vocational education in the perspective of rural revitalization is put into use. [ABSTRACT FROM AUTHOR]

At present, the basic pension insurance system for urban and rural residents in China has played a positive role in guaranteeing the basic life of the elderly in urban and rural areas. At present, the basic pension insurance system for urban and rural residents is not perfect, and there is still a great lag in the formulation of cross-system and cross-regional policies. There are differences in treatment between groups, between regions and between urban and rural areas. The coverage is not comprehensive enough and there are still some people who are not included in the basic protection system, etc. People urgently need a social pension insurance system that can provide reliable and sustainable protection in their old age. The operational efficiency evaluation of urban and rural residents' basic pension insurance systems is viewed as the multi-attribute decision-making (MADM). In this paper, the triangular fuzzy neutrosophic numbers grey relational analysis (TFNN-GRA) method is built based on the traditional grey relational analysis (GRA) and triangular fuzzy neutrosophic sets (TFNSs). Finally, a numerical example for operational efficiency evaluation of urban and rural residents' basic pension insurance systems has been given and some comparisons are used to illustrate advantages of 2TLNN-GRA method. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution, represented by intelligence, networking and greening, is breeding and breaking through, and China is increasingly Focus on green development, public awareness of environmental protection, and small changes are able to fundamentally change our industrial organization. The equipment manufacturing industry is an industry to which our country attaches great importance, and equipment manufacturing enterprises, as microscopic subjects, want to contribute to the "13th Five-Year Plan". Equipment manufacturing industry is a highly valued industry in China, equipment manufacturing enterprises as a microscopic subject, in order to the "Thirteenth Five-Year Plan" equipment manufacturing industry rose to inject a strong impetus, must make essential changes, embrace the green economy, green development, and enhance the green competitiveness of enterprises. The green competitiveness evaluation of equipment manufacturing enterprises is the classical multiple criterion group decision making (MCGDM). In this paper, depending on the Taxonomy method, Taxonomy method will be extended to picture 2-tuple linguistic sets (P2TLSs) to address some MCGDM issues. Some essential concepts of picture 2-tuple linguistic sets (P2TLSs) are briefly reviewed. In addition, integrating the Taxonomy method with P2TLSs, the Taxonomy method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application for green competitiveness evaluation of equipment manufacturing enterprises has been offered to demonstrate this novel method and some comparative analysis are also made to confirm the merits of developed method. [ABSTRACT FROM AUTHOR]

Business English teaching quality evaluation Business English is a new type of composite specialty, which is a discipline innovation made by China's higher education to adapt to the new market demand and international standards since the reform and opening up. Over the past 20 years, it has cultivated a number of compound talents for the cause of China's reform and opening up. However, the backwardness of business English theoretical research has greatly restricted the development of business English. At present, Business English has been officially approved as a new major for undergraduate enrollment by the Ministry of Education of the People's Republic of China. Its subject nature, specialty structure, training objectives, and specialty compound characteristics need to be qualitatively studied theoretically. The business English teaching quality evaluation is viewed as the multiple attribute decision making (MADM) issue. In this paper, we connect the geometric Heronian mean (GHM) operator and power geometric (PG) with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic power geometric HM (G2TLNPGHM) operator. Then, the G2TLNGHM operator is applied to deal with the MADM problems under 2TLNNs. Finally, an example for business English teaching quality evaluation is used to show the proposed methods. Some comparative analysis and parameter influence analysis are fully given. The results show that the built algorithms method is useful for business English teaching quality evaluation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore how port enterprises can scientifically select a better logistic service provider (LSP) to achieve a high efficiency. An empirical study is conducted to verify the effectiveness of the combination weighting-grey synthetic decision-making method by helping the LSP selection of a port enterprise in China. Data are collected from questionnaires administered to port logistics' industry professionals. The method is proposed, which associates the analysis network process method with the entropy method to determine the combined weights of the evaluation indexes. The improved centre-point triangular whitenization weight function is introduced to cluster the alternative port LSPs and judge the corresponding grey classes. Subsequently, the synthetic weighted decision-making vectors are used to determine the grey synthetic decision-making coefficient vectors. The grey synthetic clustering decision-making coefficients are calculated to establish a synthetic decision-making rank of the alternative plans. The combined method can help the port enterprises realize the selection of better LSPs in a scientific manner. [ABSTRACT FROM AUTHOR]

In the practice of COVID-19 prevention and control in China, the home quarantine policy directly connects and manages the residents, which plays a significant role in preventing the spread of the epi-demic in the community. We evaluate the effectiveness of current home quarantine policy in the actual execution process based on the evolutionary game relationship between the community and res-idents. This paper establishes a double-layer coupled complex network game model, and uses the multi-agent modeling method to study the game relationship between the community and residents in the context of home quarantine policies. The results show that initial strategy of the community with strict supervision and reasonable government reward allocation will increase the proportion of the residents complying with the quarantine rule. When 80% of the communities chose to supervise strictly at the beginning, people are more likely to follow the rules. While when the residents can only get 20% of the government's reward, the proportion of choosing to violate the quarantine rules is much higher than that when they can get 80% of the reward. Besides, the structure of small-world network and environmental noise will also affect the residents' strategy. As the probability of reconnection of the small-world network rises from 0.2 to 0.8, the proportion of residents who choose to comply with the strategy becomes much higher. When the environmental noise reaches 0.5, the ratio of residents who choose to violate the strategy is higher than the ratio of complianc. The study is helpful to provide the basis for the government to formulate the quarantine policy and propose an optimization for making effective quarantine measures. In this way, the government can adjust the parameters to make residents achieve the possible level of compliance with quarantine policies as high as possible to contain the spread of the epidemic. [ABSTRACT FROM AUTHOR]

In order to alleviate the increasingly serious traffic congestion problem in China, realize intelligent traffic control, and provide accurate and real-time traffic flow prediction data for traffic flow guidance and traffic travel, this paper designs a GPS-based vehicle trajectory fusion optimization deep model BN-LSTM-CNN which makes full use of the temporal and spatial correlation characteristics of dynamic traffic flow to improve the accuracy of short-term traffic flow prediction. The parameters of the historical GPS dynamic trajectory of the traffic network link are converted into a two-dimensional matrix image of time and space relationship. First, the spatial features are input to the CNN network, and the spatial dependence relationship between the links is mined, then the traffic flow time series modeling is performed with a four-layer ConvLSTM network, and the BN normalization layer is added to normalize the activation value of the previous layer on each batch, so that the model can obtain higher training accuracy and quickly complete the prediction of the traffic flow state in a certain period of time in the future. The experimental results show that the prediction model is fast to optimize, the prediction error is the smallest compared with other methods, and it can meet the real-time requirements of urban traffic control. [ABSTRACT FROM AUTHOR]

Based on the nonlinearity of energy consumption systems and the influence of multiple factors, this paper presents a nonlinear multivariable grey prediction model with parameter optimization and estimates the parameters and the approximate time response function of the model. Next, a genetic algorithm is applied to optimize the nonlinear terms of the novel model to seek the optimal parameters, and the modelling steps are outlined. Then, to assess the effectiveness of the novel model, this paper adopts Chinese oil, gas, coal and clean energy as research objects, and three classical grey forecasting models and one time series method are chosen for comparison. The results indicate that the new model attains a high simulation and prediction accuracy, basically higher than that of the three grey prediction models and the time series method. [ABSTRACT FROM AUTHOR]