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The rapid development of e-commerce international trade has driven the rapid growth of the economic system of international trade enterprises. This also means that industry competition is gradually intensifying, which also makes performance evaluation the key to cross-border e-commerce international trade. At present, my country's research on the performance evaluation of cross-border e-commerce international trade is in a blank state. Therefore, this paper takes the international trade performance evaluation of cross-border e-commerce as the research object and, based on the deep neural network model, develops a cross-border international trade performance evaluation model, changes trade strategies, and improves trade performance. This paper first analyzes various neural network models, such as artificial neural network, "BP" neuron model, and LSTM neural network. This paper summarizes a deep neural network model that is conducive to the development of cross-border e-commerce and points out the problems in the current performance evaluation of cross-border e-commerce international trade: the e-commerce market supervision system is not perfect; the second is the inconsistent evaluation indicators; the third is the evaluation system. There are some differences with the actual. Finally, this paper puts forward relevant suggestions for the performance evaluation of cross-border e-commerce international trade and points out the advantages and disadvantages of various neural networks, as well as their roles in cross-border e-commerce performance evaluation, and compares these neural networks through experiments. Experiments show that among these neural network models, the deep neural network model is the best and has the highest accuracy and stability in e-commerce trade performance evaluation. In the later stage, we will improve the global logistics system, strengthen the application of big data technology, and improve the overall performance of global operations. First, a set of indicators is designed to evaluate the performance of e-commerce systems, using the enterprise key factor model concept. In addition, this evaluation method is different from the commonly used expert evaluation method and physical evaluation method in evaluating the construction quality, cost, education and growth ability, and performance level of the international business system of cross-border e-commerce. [ABSTRACT FROM AUTHOR]

In today's economic globalization and artificial intelligence modern society, the rapid economic growth mainly relies on the vigorous development of digital information technology. Simultaneously, digital technology promotes economic revolution and produces a digital economy, which has become an important concept of China's economic development. In order to more scientifically and accurately describe the development status of my country's industrial structure and digital economy industry, this paper takes each industry of the national economy as the research object and puts forward the idea of using complex network theory to study the relationship between input and output. Based on the complex network theory, this paper analyzes the interrelationships between various industries in the complex system. By referring to the relevant data of the national economic input and output in recent years, the input-output correlation network model between the various industries in the national economic system is established. Using the method of combining statistical analysis and comparative analysis, quantitative analysis and qualitative analysis, carry out detailed and in-depth statistical analysis from the input-output correlation network model and model attributes so as to point out the status and role of various industries in the national economy and so as to analyze and study the industrial structure of the national economy. [ABSTRACT FROM AUTHOR]

In order to improve the evaluation effect of the economic and social development pioneer area, this paper constructs the evaluation index system of the economic and social development pioneer area based on the spatial network structure analysis method and obtains an intelligent analysis system. Moreover, from the perspective of economic development information flow, this paper uses information flow direction analysis method and advantage flow analysis method to discuss the structural characteristics of urban economic development network in the economic belt, providing new methods and perspectives for the study of urban economic development flow. In addition, this paper attempts to propose a universal method for quantitative research on the "flow space" structure of urban economic development as the forward-looking content of urban economic development. According to the simulation test results, it can be seen that the evaluation index system of the economic and social development pilot area based on the analysis of the spatial network structure proposed in this paper has a good effect. [ABSTRACT FROM AUTHOR]

Research Background and Content. Intellectual property and high-quality economic development are mutually reinforcing and restrictive, China is a large but not a strong intellectual property country, and China's high-quality economic development still has problems of inadequacy and imbalance. Based on the above research background, this paper mainly studies the relationship between the intellectual property system and the high-quality economic development system from the perspective of coupled and coordinated development. Research Objective. The objective is to measure the coupling and coordination degree between the intellectual property development system and the high-quality economic development system and to explore the spatiotemporal characteristics and differences in the coupling and coordination between the two systems. Research Method. Based on the data of 30 provinces (autonomous regions and municipalities) from 2013 to 2020, the methods used in this paper to analyse include entropy weight method, grey correlation analysis, coupling coordination degree model, and Dagum Gini coefficient. Research Results. The development of economic openness and innovation are more closely related to the development of intellectual property, and the protection, utilization, and creation of intellectual property are more closely related to high-quality economic development; the coupling coordination degree of the two systems shows the characteristics such as "high in the east and low in the west" and "coastal area is better than inland," and the development of intellectual property lags behind the high-quality economic development; the coupling and coordination degree of the two systems shows a slight growth trend in most provinces, but the overall differences shows an expanding trend, and differences between regions are the main sources of overall regional differences. Research Innovation. Research innovation is to study the two-way relationship between intellectual property and high-quality economic development and to measure the coupling and coordination degree between the development system of intellectual property and the high-quality economic development system, and its spatiotemporal characteristics, regional differences, and sources of differences are analyzed. Research Value. Research value is to provide decision reference for the two-way empowerment of intellectual property and high-quality economic development and regional coordinated development. [ABSTRACT FROM AUTHOR]

Ocean economy is the sum of various industrial activities for developing, utilizing, and protecting the ocean, as well as the activities associated with it. As the globe gradually pays more attention to ocean economic growth, China, as a significant maritime country, has begun to pay attention to the sector and put up ocean economic development policies. The marine economy has great potential, and the development of the marine economy is of great significance to the economic development of China. The Fujian Province is located at the junction of the Belt and Road and the Yangtze River Economic Belt, with a unique geographical location and natural resource advantages. Analyzing the state of the ocean economy in the Fujian Province, identifying challenges, and developing ocean economic development strategies to promote the long-term growth of the ocean economy in the Fujian Province has become a pressing issue that must be addressed. Because there is currently limited research on ocean economic systems and a paucity of ocean economic data, this paper uses a deep neural network to forecast the ocean production output value of the Fujian Province. The experimental results show that the model proposed in this paper can predict the ocean invention value of the Fujian Province well, which confirms the effectiveness of the model. [ABSTRACT FROM AUTHOR]

It is of great significance to accurately predict the operation of the system economy, analyze the gains and losses of macrocontrol policies, evaluate the operation quality of the economic system, and correctly formulate the future development plan and strategy. This paper introduces the deep belief network, which has attracted much attention in the field of deep learning in recent years, into the research of system economic operation and management. This method solves the problems of slow training and learning speed, easy to fall into local minima and insufficient generalization of BP artificial neural network in the research of system economic operation and management. Taking the consumer price index and total import and export volume of F Province as the research object, the experiment proves that DBN has better application in system economic operation and management than BP neural network and vector autoregressive analysis. This paper analyzes and compares the modeling performance of DBN, BP neural network, and VaR method from many aspects, such as prediction accuracy, training convergence speed, and pretraining with or without samples. Relevant empirical results show that DBN has better economic prediction performance than BP neural network and ver. On the other hand, DBN can effectively use nonstandard samples to pretrain network weight parameters. Therefore, DBN is a better operation and management modeling means of economic system, with excellent practicability and application, and is expected to be popularized and applied in the field of economic forecasting. [ABSTRACT FROM AUTHOR]

Under the development of social economy and the gradual improvement and optimization of the financial and economic system, China's financial structure is constantly changing and evolving. Financial institutions are the interrelations and connections between the various parts of the economy as a whole. They represent the role and achievements of the financial economy. Research shows that the transformation and evolution of financial structure promotes economic development and management efficiency. Therefore, under the background of the continuous evolution of financial structure, this article explores the factors of the evolution of financial structure on economic growth and management efficiency. The results of the experiment are as follows: (1) this article investigates developments of the evolution of financial structure, economic development, and management efficiency, determines the research direction of the experiment, provides background support for the subject research of this paper, and explores the influencing factors according to the impact mechanism on economic development and management efficiency and (2) put the evolution background of the financial structure in the degree of economic development and management efficiency. By using the economic growth calculation algorithm and management efficiency calculation algorithm, calculate the change trend of the range of economic growth and the fluctuation of the degree of management efficiency under the background of the evolution of the financial structure. The experimental results show that under the background of the evolution of the financial structure, the total development of the national economy has been effectively broken through, and the management mode of enterprises has been improved to effectively improve the management efficiency. [ABSTRACT FROM AUTHOR]

Agriculture is the basic industry of the national economy, and the transformation of agricultural economic growth mode is of great significance to ensure the supply of agricultural products and improve the quality of agricultural products. Therefore, it is the only way to solve this problem to change the way of agricultural economic growth through scientific and technological investment, industrial structure adjustment, and other methods. Based on the fuzzy comprehensive evaluation method, this paper analyzes various factors of agricultural economic development and establishes a multilevel fuzzy comprehensive evaluation model of the development status of agricultural economic system. The stochastic frontier production function model of the fuzzy control comprehensive model is applied to decompose the agricultural labor productivity, and the counterfactual thinking and distribution method are used to analyze the influence of these factors on the evolution of provincial agricultural labor productivity differences. The value inequality decomposition method measures the contribution of each factor to the provincial agricultural labor productivity difference as well as the contribution of exogenous explanatory variables to the provincial agricultural technical efficiency difference. It is concluded that the relative contribution rate of nonagricultural activities to the difference in agricultural technical efficiency is the largest, and the average relative contribution rate reaches 74%. The improvement of agricultural labor productivity cannot rely solely on the increase in the input of agricultural material factors, but should rely on science and technology. [ABSTRACT FROM AUTHOR]

Objective. To carry out the research on the vulnerability evaluation and influencing factors of the tourism economic system is the objective requirement of formulating the scientific development strategy of the tourism economy and improving the quality of regional tourism development. Methods. Based on the vulnerability analysis of tourism economic system based on BP neural network (BPNN), this paper takes the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the research object and selects 14 index data. The mean and standard deviation of the calculated weight values are used to formulate evaluation criteria for the tourism system. Results. The BP neural network (BPNN) model was used to predict the distribution law of vulnerability data within the standard range of the Greater Bay Area after 2020, obtained the spatial distribution law of vulnerability in the geographic structure distribution of the Greater Bay Area, and determined the vulnerability analysis framework and evaluation method. Conclusion. The cities in the Greater Bay Area should first pay attention to the industrial structure; increase financial investment; enhance the attractiveness of tourist destinations, in-depth development of tourism resources, and rational design of tourism products; help reduce the vulnerability of the tourism economic system; and improve regional self-recovery capabilities. [ABSTRACT FROM AUTHOR]

In order to improve the effect of e-sports training, this paper combines the intelligent gesture recognition technology to construct an e-sports training system and judges the training effect of players through the recognition of players' gestures. Moreover, this paper studies the commonly used feature extraction algorithms and proposes an improved SLC-Harris feature extraction algorithm, and the feasibility of this algorithm is verified by the experimental results on the EUROC data set. In addition, this paper uses the KLT optical flow algorithm to track the extracted feature points and calculates the pure visual pose through epipolar geometry, triangulation, and PnP algorithms. The experimental research results show that the electronic economic training system based on intelligent gesture recognition proposed in this paper has certain effects. [ABSTRACT FROM AUTHOR]

At present, in order to adapt to the development of the era of big data, more and more industries use the concept of big data, and the economic and financial management system is no exception. In the context of the concept of big data, the campus economy has also ushered in new opportunities and challenges. Combined with the basic knowledge of big data, this paper makes a systematic research on industrial economic information analysis, which will contribute to the application practice of industrial big data. Using the value of big data will promote revolutionary changes in the work of the school's economic management department. Taking this as the starting point, this paper systematically analyzes the analysis methods of campus economic information under the background of big data and its role in macro decision-making. [ABSTRACT FROM AUTHOR]

The analysis of the current economic statistics system shows that the requirements for computing and storage capacity are relatively high. For the previous main controller, it is difficult to meet this basic requirement, but the application of cloud computing technology can solve this problem to a greater extent. Therefore, this paper designs a new economic analysis system based on cloud computing, which can enable small- and medium-sized enterprises to master the business information transmitted by customer economy and improve the quality of monitoring service. Experiments in this paper show that the designed system can reduce the cost of remote communication, interact with SMS, and realize dual channel communication. [ABSTRACT FROM AUTHOR]

In recent years, under the background of stable economic operation, people's research on economic systems has become increasingly popular. The dynamic input-output model reflects the change and development process of the input-output relationship of the economic system over a period of time. The main purpose of tracking control is to design a suitable controller so that the output of the control system can track the output of the reference system as much as possible. In the economic system, data is an important factor. Based on this, this paper mainly studies the tracking control of dynamic input-output economic system based on data fusion. This research takes the data fusion of the dynamic input-output economic system as the starting point and takes the optimal control and tracking of the economic system as the research object of this research. Based on data fusion technology, a new dynamic input-output economic system tracking and control is proposed. This paper studies the finite-time optimal tracking control of linear systems. Through numerical examples, comparing the finite-time and infinite-time optimal control simulation results, it is proved that the algorithm can achieve good tracking control. Experimental data shows that the optimal and suboptimal performance indicators for a limited time are 0.7729412 and 1.5687310, respectively. Therefore, compared with the infinite-time optimal control, the performance loss and the final tracking error of the suboptimal control proposed in this study are reduced. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of the modern economy, information is particularly important in the economic field, and information determines the decision-making of enterprises. Therefore, how to quickly dig out information that is beneficial to the enterprise has become a crucial issue. This topic applies data mining technology to economic intelligent systems and obtains the data object model of economic intelligent systems through the integration of information. This article analyzes the interrelationship between its objects on this basis and uses data mining-related methods to mine it. The establishment of economic intelligence systems not only involves the establishment of mathematical models of economic systems, but also includes research on the algorithms applied to them. How to apply an algorithm to quickly and accurately extract the required economic intelligence domain information from the potential information in the database, or to provide a method to find the best solution, involves the use of association rules and classification prediction methods. The application of data mining algorithms can be used to study the application of economic intelligence systems. This paper develops and designs an economic intelligence information database and realizes the economic intelligence system on this basis, and realizes the research results. Finally, this paper has tested the dataset, and the results show that the classification accuracy of this algorithm is 2.64% higher than that of the ID3 algorithm. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth analysis and study of the spatial effects of financial support and economic growth with the help of nonlinear generalized complex systems. Taking the industrial sector as the research object and combining the relevant contents of neoclassical investment theory, information economics, and institutional economics, this paper clearly defines and argues that the main feature of current financial policy is financial constraint rather than financial inhibition based on an in-depth understanding of the theoretical connotation and policy rationality of financial constraint and, as a premise, further analyzes the financial constraint policy causing excessive investment and capital mismatch in the corporate sector. It further analyzes the mechanism of the role of financial constraint policies in causing overinvestment and capital mismatch in the corporate sector and conducts empirical tests from three research perspectives of measuring investment efficiency, output efficiency of investment, allocation efficiency of industry capital, and investment behavior of microenterprises, and finally puts forward relevant policy recommendations in conjunction with the evaluation of the efficiency of financial constraint policies. This paper selects three dimensions of the financial system, namely, financial structure, financial efficiency, and financial scale, and studies the adaptability between these three dimensions and the development of the real economy, respectively, and then uses different empirical methods to analyze the dynamic adaptability effects between the development of the real economy and these three dimensions of the financial system and finally explores the way of adaptability between the financial system and the development of the real economy. This paper provides a medium and micro theoretical basis and new empirical evidence for understanding the importance of financial system reform on economic growth and also opens up a space for exploring the exit path of financial constraints and using interest rate marketization as a general grip to reasonably guide financial resources to achieve economic transformation and upgrading and sustainable and healthy development through supporting high-quality investment, using more interprovincial level data in the analysis, so it is more comprehensive and detailed than previous scholars' studies. The examination is more comprehensive and detailed than previous scholars' studies. [ABSTRACT FROM AUTHOR]

In the new era, China's economic development is in the offensive period of transforming the development mode, green development is an inevitable requirement to accelerate the transformation of economic development mode and optimize the industrial structure, and we should adhere to the concept of ecological priority and green development to promote high-quality economic development. The 19th Party Congress clearly proposed to "promote green development, establish a sound economic system of green low-carbon cycle development, and build a market-oriented green technology innovation system." Green technology is the technology to save resources, reduce pollution, and achieve sustainable development. Green technology innovation continues to promote green development, which will become an important support to promote the progress of ecological civilization, adhere to pollution prevention and control, and promote high-quality development. Promoting green technology innovation, taking the road of sustainable development, enhancing the awareness of environmental protection, and promoting high-quality economic development are also inevitable choices to promote the conversion of economic development mode. Carrying out research on the impact of green technological innovation on regional economic growth is of great significance to alleviate the shortage of innovation resources in China, guide enterprises to change to a green way of development, and promote the sustainable development of China's economy and population, resources, and environment. This paper provides publicly available data from 2015-2021, takes fixed asset investment as the variable, introduces control variables, and analyzes the relationship between technological innovation and economic growth using fixed-effects model and intermediate-effects model. The results show that innovation contributes significantly to regional economic growth and is influenced by the mediating role of fixed asset investment. In order to boost China's economic growth, specific policy recommendations are proposed in terms of optimizing the regional innovation layout, improving the intellectual property rights system, cultivating high-quality talents, optimizing the structure of fixed assets, and attracting the inflow of foreign capital. [ABSTRACT FROM AUTHOR]

Based on the SURF algorithm, the PROSAC (Progressive Sample Consensus) algorithm is first used to delete a large number of matching points to improve the accuracy of remote sensing image registration and to improve the speed of the SURF algorithm. Finally, PROSAC geometric verification is used in the study area to achieve accurate image stitching. In the field of computer economic auditing, there is a serious disconnect between theory and practice. As the company's electronic data becomes more and more abundant, the method of determining its authenticity has become an important issue that auditors need to solve immediately, and special research on the theory of data reliability is needed in the field of computer economic auditing. In this article, we will first introduce the background and practical significance of project development, explain system-related development technology, conduct system analysis and system design of the project, and discuss the effectiveness and economic benefits of project development technology. Detailed analysis and description of system design include system function module processing and system database design. The innovation of this paper is that the system can meet the actual financial and auditing needs of very professional enterprises. In addition, the work documents required for the audit are automatically generated according to the work requirements, which can completely clarify the responsibilities of each department and comprehensively improve the audit efficiency. At the same time, the entire system is safe and orderly, which can ensure the normal operation of the operation. The purpose of this article is to explore database-based natural language query technology. First, after introducing the database intelligent language, we will study the Chinese word segmentation and part-of-speech tagging algorithm based on HMM to explain the details of the continuous field matching algorithm. [ABSTRACT FROM AUTHOR]

To promote urbanization in the next stage, it is of great significance to explore the ecological efficiency of green ecological regions and advance the sustainable development of a social economic system. However, spatial heterogeneity has not been fully considered in the existing evaluation models or methods for regional ecological efficiency (REE), and the corresponding decisions on sustainable development are not the optimal solutions. To solve the problems, this paper explores the evaluation of REE and intelligent decision support for sustainable development by analyzing environmental big data. Firstly, the spatiotemporal evolution of REE was examined based on environmental big data to clarify the spatial layout of REE and the sources of the spatial differences. Next, a multiobjective optimal decision-making model was established for the sustainable development of a regional ecosystem, and the solving method was presented for the model. The proposed model was proved valid through experiments. [ABSTRACT FROM AUTHOR]

The vulnerability assessment indicator system (VAIS), including the tourism economic sensitivity and respondence, is modified and established in this paper. According to the collected data, during 2014–2018 of the 31 provinces of China, of the tourism economy sensitivity and respondence, the improved comprehensive evaluation projection pursuit clustering (PPC) model is established, and the vulnerability indexes of the 31 provinces are calculated, thus expanding the tourism economic vulnerability assessment methods. Our empirical results show that, during the period of 2014 to 2018, the sensitivity, the respondence, and the vulnerability indexes are unbalanced overall. The tourism economy sensitivity and the respondence show that the spatiotemporal distribution characteristics are high in the east and low in the west. On the contrary, as for the vulnerability, the spatiotemporal distribution characteristics are low in the east and high in the west. Among the 40 indicators, the ratio of industrial solid waste utilized (%), urbanization rate, and the density of grade highway and railway network (km/km2) have the greatest impact on the respondence, while the proportion of the population affected by natural disasters, the diversification index of industrial structure, and the number of traffic accident casualties have the most significant impact on the sensitivity, which are the indicators that have the greatest impact on vulnerability. Therefore, in order to effectively reduce sensitivity, improve respondence, and thus reduce the vulnerability index of the tourism economy, the provinces should first improve the above-mentioned evaluation indicators with the largest weights. Our research results in this paper enrich the theory of sustainable development of the tourism industry and derive managerial and policy insights for further achieving the high-quality development of the tourism economy. [ABSTRACT FROM AUTHOR]

Transnational investment is featured by its large scale and high risks. During transnational investment, the frequent risks often bring a huge loss to the investors. Therefore, the risk factors should be included in the economic evaluation of transnational investment projects. However, the existing evaluation models and systems are rather complex, lacking a unified framework. Besides, there are few practical applications of these models or systems. To solve the problem, this paper explores the factors and economic evaluation of transnational investment risks. Firstly, an economic evaluation system was constructed for transnational investment projects, and the economic evaluation result was depicted in two aspects: economic income factors and investment risk factors. Then, the applicability and economic meanings of common indices were clarified one after another. After that, the economic evaluation flow was designed for risk-based transnational investment projects. Finally, an economic evaluation was performed on actual projects, which verifies the feasibility of the proposed evaluation method. [ABSTRACT FROM AUTHOR]

The research on logistics heat facilitates the understanding of the drivers of regional logistics development. However, many scholars ignore the difference between prediction methods in terms of attributes and focal points of data analysis during the selection of regional logistics heat prediction model. Regional logistics interacts with regional economy. However, the studies on the coupling development between the two systems fail to make a detailed analysis in the light of their actual situation. Therefore, the evaluation of the coordination degree is often biased. To solve the problem, this paper probes into the prediction of regional logistics heat and the coupling development between regional logistics and economic systems. Firstly, an index system was established to measure the level of coupling development between the two systems, and a grey relational analysis was performed on the indices, leading to the evaluation results on coordination degree. Next, a composite model of GM (1, 1) and backpropagation (BP) neural network was proposed, and the deviation interval of the composite predictions was predicted based on Markov chain prediction model. The proposed algorithm proved effective through experiments. [ABSTRACT FROM AUTHOR]

The existing fuzzy assistant cognition system has the problem of imperfect retrieval function, which leads to long execution time. This paper designs a fuzzy assistant cognition system of international economic and trade information under supply chain management. Hardware Part. Optimize wireless sensor and connect power interface and related accessories. In the software part, the dynamic characteristics of international economic and trade information elements are extracted, the flexible operation model of supply chain management is constructed, the demand-oriented organizational structure is established, the output set is determined by the product reasoning, and the retrieval function of fuzzy assistant cognitive system is designed by using the fuzzy association algorithm. Experimental Results. The average execution time of the fuzzy assistant cognitive system and the other two systems is 123.593 s, 165.733 s, and 169.506 s, which proves that the cognitive system integrated with supply chain management has a higher practical application value. [ABSTRACT FROM AUTHOR]

There is a close correlation between regional economy, tourism, and exhibition industry. By constructing a system of evaluation indicators for the regional economy, tourism industry, and exhibition industry, the coupled coordination degree model was used to calculate the degree of synergy of the regional economy, tourism industry, and exhibition industry in China from 2013 to 2019. In addition, the influencing factors of the degree of synergy were analyzed by gray correlation analysis. As shown by the results, the comprehensive development scores of regional economy, tourism industry, and exhibition industry show an overall growth trend, while the development level index presents a spatial distribution pattern of decreasing gradient from coastal area to inland in space. Apart from that, the integration and development of regional economy, tourism industry, and exhibition industry show a continuous coordinated and benign development. On a national scale, the degree of integration of the regional economy-tourism industry-exhibition industry in China has gradually developed and improved from bare coordination to good coordination. Besides, the degree of coupling and coordination of regional economy-tourism-exhibition industry varies greatly among provinces. Moreover, all the indexes have a strong impact on the coupling and coordination degree of the regional economy-tourism industry-exhibition industry. Compared with the exhibition industry system, the economic system and tourism system have a stronger impact on the coupling and coordination degree of the regional economy-tourism industry-exhibition industry. [ABSTRACT FROM AUTHOR]

The development of medical detection, storage, and other technologies makes China's medical and health field accumulate massive data. Big data analysis technology can mine and analyze these data and establish medical information systems to enhance hospital treatment and service levels. Therefore, this work studies the construction and application of medical economic information systems. Specifically, neural networks, as a means to handle a large number of medical economic data, and has received great attention. This work uses BP neural network to extract the medical economic information feature, which is a big data technology and can extract deep features of data, after that, we compare and analyze the characteristic of different medical data. Finally, we establish the medical economic information system for the follow-up medical diagnostic services. [ABSTRACT FROM AUTHOR]

Given the intricate interactions among the economy, land use, and transportation, it is important to assess the multifaceted impacts of the freight corridor on these systems. This study introduces a land‐use transport interaction (LUTI) modeling approach to quantify the scope and magnitude of the impact of a railway corridor on the distribution of freight flows within an intermodal service network and industrial locations. The proposed model operates on two levels to analyze regional interactions between industrial locations and transportation dynamics. The upper‐level model simulates the industrial interactions among regions. Meanwhile, at the lower level, interregional trade connections are converted into freight demand, which is then assigned to a transportation network. Calibration of the trip length distribution is achieved by integrating data from truck GPS, railway waybills, and ship visas to develop a connection between the intermodal service networks and economic systems. The improved model offers a LUTI modeling approach tailored for the context of intermodal transportation, considering economies of scale associated with intermodal transportation services. It can not only analyze the impact of a freight corridor on freight flow redistribution but also identify areas that may be adversely affected by such redistributions. Taking the Yangtze River Economic Belt (YREB) as a case study, study results indicate significant enhancements in the economies of scale of railway services within the middle part of the YREB due to the development of the Haoji Railway Corridor (HRC). These changes significantly influence the location utility of industrial activities, with the coal processing activities demonstrating the most sensitivity to the evolving transportation dynamics. This study offers insights into LUTI modeling approaches specifically tailored for intermodal transportation. [ABSTRACT FROM AUTHOR]

With the continuous development of the world economy, the development and utilization of environmentally friendly and renewable energy have become the trend in many countries. In this paper, we study the dynamic economic dispatch with wind integrated. Firstly, we take advantage of the positive and negative spinning reserve to deal with wind power output prediction errors in order to establish a dynamic economic dispatch model of wind integrated. The existence of a min function makes the dynamic economic dispatch model nondifferentiable, which results in the inability to directly use the traditional mathematical methods based on gradient information to solve the model. Inspired by the aggregate function, we can easily transform the nondifferentiable model into a smooth model when parameter p tends to infinity. However, the aggregate function will cause data overflow when p tends to infinity. Then, for solving this problem, we take advantage of the adjustable entropy function method to replace of aggregate function method. In addition, we further discuss the adjustable entropy function method and point out that the solution generated by the adjustable entropy function method can effectively approximate the solution of the original problem without parameter p tending to infinity. Finally, simulation experiments are given, and the simulation results prove the effectiveness and correctness of the adjustable entropy function method. [ABSTRACT FROM AUTHOR]

Traditionally, water governance focuses on water only. The emergence of virtual water breaks this limitation and integrates economic and social systems with the water resource system. This paper establishes an interprovincial complex network of virtual water flows in China, based on the theory on complex network, which has rarely been adopted to study the virtual water transfer network. Then, the authors analyzed the pattern and evolutionary features of China's interprovincial virtual water flow network. In this way, the complex network theory was successfully applied to explore the virtual water flows across provinces in China. [ABSTRACT FROM AUTHOR]

To determine the development mode of layered sandstone reservoir, a system economic model was established, which thought the layer in production and its upper (downer) layer as a system, and the overall benefits of the two modes were contrasted using the existing well (UEWM) or the method of drilling a new well (DNWM); then, the upper (downer) oil layer development mode could be determined quickly by the model. The method can avoid the chemical agent effect of the upper target layer, which also makes the calculation more accurate. In the model, the cumulative oil production limits of the producing layer are described at different oil prices of DNWM and UEWM methods. Then, an economic ultimate water cut (EUWC) model is established. According to this model, when the water cut attains to EUWC, the oilfield should be abandoned. Meantime, the arctangent prediction model for water cut is combined with the water drive curve method, to forecast the accumulative oil from the planning time of the upper target layer production to the abandonment time of the first production layer of oilfield. And then, the development mode could be decided through contrast with the cumulative oil production limit. When the oil price is 40$/bbl, the EUWC of the block is 97.55%, and time is May 2020, earlier than the planned upper layer production time January 2023, so its rest cumulative production would be 0.0 × 10 4 t , which is less than the cumulative production limit of 32 × 10 4 t. Hence, the UEWM should be chosen. When the oil price is $70/bbl, EUWC is 98.93%, and the corresponding time is August 2027. From the planned return time of January 2023 to August 2027, the block has cumulative oil production of 25.54 × 10 4 t , greater than the cumulative oil limitation of 10.8 × 10 4 t. The old exiting well still has larger economic productivity; hence, the DNWM method should be chosen. This work provides theoretical support for up (down) formation development mode of production layer. It is of great significance to guide the development of layered sandstone reservoirs. The system economic model established can decide development mode with drilling wells or using exiting well, and it was first created in the field of oil reservoirs. This method fills up the theoretical blank of development mode for upper or downer layer of the producing layer in layered sandstone reservoir. [ABSTRACT FROM AUTHOR]

The steady and healthy development of strategic emerging industries (SEI) can enable the Republic of China to smoothly transform its economic progression mode and realize the upgradation and optimization of its industrial organization. In this way, China can take the initiative in the process of globalization. The strategic emerging industry economy has long argued for the influence of resilient firm dynamic aptitudes on innovative product growth. This study takes strategic emerging industrial economies as an important part and establishes a comprehensive evaluation index system for economic efficiency of SEI in the Republic of China from the perception of interorganizational interactions and entrepreneurial coordination features. We use the Random Forest (RF) algorithm to perform multifeature fusion and establish an economic efficiency measurement algorithm for SET through survey data from several Chinese companies. We find, in addition, that entrepreneurial coordination affects the firms' inclination and aptitude to exploit relationship profits and by this means significantly strengthening the effects of vertical interactions however weakening the effects of horizontal interactions. When compared with the BP and MLP approaches, the suggested approach has achieved 86.98% accuracy, while the other has 86.02% and 85.75%, respectively. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises (SMEs) play an indispensable role in China's national economic system, and they can play a critical role in promoting economic growth and full employment. The main reason for the disruption and impediment to the development of SME clusters is that the enterprises in the clusters are experiencing a "capital shortage," as a result of the double contradiction between the clusters' financial benefits and the difficulties in financing. Grey theory is a relatively new concept in the field of information processing. It proposes theories and methods for processing and analyzing incomplete information systems using mathematical methods. This study uses finance in supply chain as a new research perspective to investigate the effectiveness of finance in supply chain in resolving SMEs' financing problems using the Grey theory model, with the goal of resolving SMEs' financing problems. When comparing the results of the Grey theory model and the regression analysis model, the relative error of the Grey theory model is on average 12.2% lower than that of the regression analysis model, indicating that the Grey theory model greatly improves accuracy. As a result, using the Grey theory model to solve supply chain financing and SMEs' difficulties can share risks, share credit, reduce transaction costs, weaken information asymmetry, and achieve mutual benefits and a win-win situation. It is expected to promote the development of the finance in supply chain model, mobilise enterprise enthusiasm for using finance in supply chain, improve finance in supply chain operational efficiency, and promote finance in supply chain development. [ABSTRACT FROM AUTHOR]

In order to effectively reduce the risk of construction project (CEP) and maximize the benefit of CEP, this study establishes the construction project economic evaluation (PEE) system by using computer technologies such as transfinite learning machine, artificial intelligence algorithm, and related fuzzy neural network and compares the coupling and sensitivity of different algorithms for PEE indicators, Through the demonstration of the comprehensive efficiency of the PEE system under the condition of computer technology, The results show that the index coupling and early warning sensitivity of the project economic evaluation system using the artificial intelligence algorithm of overlimit learning machine under computer technology are better than the previous traditional algorithms, which can realize the artificial intelligence of the economic evaluation system, reduce the investment cost of the project and improve the delivery time of the project, make the best balance between the technical application and economic operation of the project, and promote the sustainable development of the construction project. [ABSTRACT FROM AUTHOR]

The economic strength of a country is the external manifestation of its comprehensive national strength. In order to increase a country's international influence, it must strengthen its own economic development. China's economy is in a period of rapid development. At this stage, enterprise development is an important factor in promoting steady economic growth. However, economic management plays an important role in the development of an enterprise. Therefore, how to use effective economic management methods to promote the development of enterprises is very important. This method helps to enhance the competitiveness of enterprises and improve the economic efficiency of enterprises. This approach needs to get people's attention. For productive enterprises, the biggest problem is that the economic benefits are not up to expectations. In addition, spending costs are always well over budget. In fact, this has a lot to do with business management. Before the market, economic system was reformed. The comprehensive management of productive enterprises is mostly extensive management. This makes the economic costs of certain links and details out of control. Therefore, effective management of the economy of a productive enterprise is critical. Although productive enterprises cannot be said to be highly profitable, their economic benefits are at least achievable. For productive enterprises, the most effective management method for the economy is refined management. This article starts from the perspective of improving the speed of enterprise development. Specifically, the starting point is to promote the improvement of the country's comprehensive national strength. The article analyzes the inherent relationship between economic management and enterprise development, hoping it can provide positive help for China's social and economic progress. [ABSTRACT FROM AUTHOR]

We can observe self-organization properties in various systems. However, modern networked dynamical sociotechnical systems have some features that allow for realizing the benefits of self-organization in a wide range of systems in economic and social areas. The review examines the general principles of self-organized systems, as well as the features of the implementation of self-organization in sociotechnical systems. We also delve into the production systems, in which the technical component is decisive, and social networks, in which the social component dominates; we analyze models used for modeling self-organizing networked dynamical systems. It is shown that discrete models prevail at the micro level. Furthermore, the review deals with the features of using continuous models for modeling at the macro level. [ABSTRACT FROM AUTHOR]

This study constructs a coupling model and establishes an index system for the coupled and coordinate development between cross-border e-commerce supply chain system and economic system. The index system adopts supply chain, foreign trade, e-commerce, e-commerce logistics, economic development, social consumption, talent environment, and technological innovation as sequential covariates. The calculation shows that the first three batches of 35 cross-border e-commerce comprehensive pilot areas (CBECCPA in brief) in China, in 2017, are classified into three degrees of the coupled and coordinated development: superior, good, and moderate. The study provides useful recommendations for promoting cross-border e-commerce supply chain, such as to pursue high-quality balanced development, to cultivate professional composite talents, to encourage innovation and entrepreneurship, and to create a favorable economic environment. [ABSTRACT FROM AUTHOR]

In order to improve the economic management effect of large enterprises, a decision support system for economic management of large enterprises based on artificial intelligence is designed. The system hardware and software are designed, respectively. The system hardware consists of basic information module, business management module, personnel management module, salary and welfare management module, system management module, and database module. With the support of artificial intelligence technology, build a BP neural network model, and the model was trained, through continuous learning rate adjustment; in the process of training error lower sales forecast results, according to the result of prediction in enterprise comprehensive benefit maximization as the goal, set up large enterprises economic management decision-making model, large enterprise economic management decision-making algorithm design. The test results show that the system has good fault tolerance, reliability, robustness, and high efficiency, the system response time is short, the decision accuracy is high, and the practical application effect is good. [ABSTRACT FROM AUTHOR]

In order to study the driving force of China's rapid economic development in the past ten years, the study takes Guizhou, Yunnan, and Guangxi as a case study, focusing on the big data assets exchange (GBDEx) and Beibu Gulf Economic Zone, and discusses the impact of Internet plus economic and government data and the big data system on regional economy. Finally, it is believed that the Internet and big data fully avoid the disadvantages of traffic distance between the western region and the eastern region, make full and efficient cooperation between enterprises and institutions in the central and western regions and Chinese and foreign economic entities, and strengthen the control of economic behavior from the big data level with the support of the service-oriented government. The information entropy output from the Internet big data system has led to a significant entropy reduction process in China's economic environment and a more orderly economic system, which is also an important reason for the rapid development of China's economy. [ABSTRACT FROM AUTHOR]