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At present, the development of China's economy is inseparable from the promotion of innovation and entrepreneurship. However, there are huge differences in the level of entrepreneurship in different regions, so it is urgent to analyze the influencing factors of entrepreneurship. This paper uses panel data of 31 provinces in 2008–2017 to test the impact of urban unemployment rate, regional financial development level, market scale, agglomeration effect, entrepreneurial cost, scientific and technological innovation level, government support and other factors on entrepreneurial level. To solve the issue of factors influencing the enterprises, we utilised an effective way of fuzzy logic along with decision estimation strategy. The empirical results show that regional financial development level, agglomeration effect, technological innovation ability, government support and so on have a positive role in promoting the level of entrepreneurship, while urban unemployment rate has no significant effect on the level of entrepreneurship. Based on the empirical conclusion, the paper puts forward some policy suggestions. [ABSTRACT FROM AUTHOR]

This paper presents a general overview and a long-term comparison in fuzzy logic research published between 1965 and 2017, obtained via Web of Science. The paper analyzes the growth, impact, trends and regional localization of fuzzy research. Conventional, sophisticated among others bibliometric indicators have applies. It aggregates the information according to different levels and criteria including researchers, publications, institutions, or countries. A global perspective have been provided through comparisons of regional aggregates and compound annual growth rates that strengthen the indicators applied in this article. The results permit to visualize the influence, importance, evolution and performance of the fuzzy research as well its contribution to, and transversality with other fields. The findings show that China continues to be a leader in number of contributions. There has been a recent relative decline in the United States contributions overall. Asian and African contributions to scientific literature have grown noticeably. The results also provide a framework for the use of indicators adjusted to specific contexts and relevant information for future research. [ABSTRACT FROM AUTHOR]

The accelerated development of urbanization in China started with economic globalization and industrialization, and also in the process of economic system transition. Generally speaking, urbanization is an important indicator of a region's economic development and social development. Urbanization equity is an important direction of sustainable economic and social development. From the economic dimension, urbanization can promote division of labor, specialization and accumulation of human capital through agglomeration effect. This paper analyzes the social equity and urbanization by using fuzzy logic and factor analysis model. Under the condition of market economy, migrant workers have no competitive advantage in the labor market because of their low educational level. At the same time, the treatment of migrant workers in social security, cultural education and economic welfare is lower than that of urban residents. Under the unbalanced economic development reality, the economic absorption effect leads to the migrant workers rushing to the developed big cities. The results shows that by taking the dimensions of social justice of the rural migrant worker as the independent variable, psychological urbanization for the dependent variable, the regression Equation of F value is 90.424, P = 0.000, less than 0.05 level of significance. Also, we make correlation analysis on all factors of social justice and urbanization. The experimental results show the effectiveness of proposed method. Green building is the development of sustainable development concept in architectural field. While the construction industry has brought great benefits to the development of national economy, its high investment, high pollution and inefficient development mode has also produced a huge energy load. Therefore, from the perspective of environmental and economic sustainability, the development of green buildings is particularly important. In this paper, the author makes economic benefit analysis of green building based on fuzzy logic and bilateral game model. By introducing such factors as economic benefits, cognition and government policies, this paper construct an evolutionary game model, which provides a basis for improving the economic benefits of green buildings. The results show that the first factor affecting enterprise decision-making is the incremental profit of green building developers, followed by the government's incentive policy. After the evolution of the market, the final strategic choice will be stabilized to higher economic benefits. Generally speaking, green buildings need to effectively control incremental costs and consider scale benefits. Through management efficiency innovation and policy stimulation, the problems of huge investment cost and long payback period can be solved, so as to improve the economic benefits of green building development. [ABSTRACT FROM AUTHOR]

At present, China has great difficulty in obtaining the reliability of teaching data sources. In order to further improve the effectiveness of data mining and reduce the difficulty of data acquisition, this paper studies the design and simulation of integrated education information teaching system based on fuzzy logic. Bayesian algorithm can perform data mining, feature recognition and classification on data in big data, so that it can effectively process massive data sources. By weighting the different network structures, the number of undirected edges in the network is reduced, and then small data sets that can be processed by multiple traditional algorithms are sampled from the big data set, and data is generated by using the Bayesian network toolkit Samiam. The modules respectively generate data sets of different sizes and construct a teaching data source generation model. The experimental results show that RSEM on Child and Alarm data can take less time and achieve an accuracy of 86.17% compared with the whole data set under the same effect. This paper proposes a Bayesian network structure integration model, which can solve the problem of data acquisition difficulties, and is also a further improvement of data mining technology. [ABSTRACT FROM AUTHOR]

The "Belt and Road" initiative (BRI) enhances the cooperation between China and countries in Central and Eastern Europe (CEE), and expands the scale of China-invested enterprises in CEE countries continuously. But it also results in the increase in investment risks. Meanwhile, large differences between the international labor market and the domestic employment environment have led to the inadaptability of some enterprises' overseas employment policies, triggering many labor disputes, and producing adverse effects on their overseas business expansion. To resolve the problems, this paper attempts to study the measures to prevent labor employment risks using fuzzy inference system for China-invested enterprises in CEE. For this, it performs analysis for the scale, structure, labor quality, wages and benefits, and labor law system of labor employment in CEE countries, and proposes to prevent and resolve the labor employment risks by strengthening government labor cooperation, familiarizing with local labor law systems, and respecting local management culture etc. [ABSTRACT FROM AUTHOR]

Based on the company cases published in China over the past ten years, both theoretical methods and Artificial intelligence technologies were applied to analysis cases data on the effectiveness of clauses restricting equity transfer in articles of association of limited liability companies (LLCs). With its unique characters based on shareholders and strong vitality, limited liability company (LLC), as the "evergreen tree" among the market players, is a company form adopted by many investors. Nevertheless, due to its prominent closed characteristics, equity transfer has become a bottleneck for the development of LLCs. According to this paper, it is necessary to distinguish between the effectiveness of clauses restricting internal and external equity transfer in articles of association of LLCs. Fuzzy Analytic Hierarchical Process (AHP) is utilized for which involves process of analytic hierarchy modelled with utilizing theory of fuzzy logic. Moreover, instead of being confined to the existing legal norms, the judgment standard of clauses restricting equity transfer in articles of association of LLCs should be comprehensively measured by the golden rules, i.e. "fairness", "autonomy" and "operability". [ABSTRACT FROM AUTHOR]

Track irregularity is the main source of vibration excitation of vehicle-track weighing system, which has an important impact on the safety, stability and comfort of train operation, and it is also the main factor limiting the speed of train operation. Higher requirements are put forward for track smoothness with the rapid development of China's railways. Therefore, it has a great theoretical and practical significance to study the relationship between track irregularity and random vibration of vehicle-track cooker-in system and the evaluation method of track smoothness. In this paper, a model construction method is proposed based on machine learning fuzzy logic control and neural network algorithm to analyze the high frequency dynamic characteristics of ballastless track wheel-rail vehicle system. Firstly, a numerical analysis model of high frequency dynamic characteristics of ballastless track wheel-rail vehicle system is established by using linear discrete elastic-yellow damper element connection model; Secondly, the Rough Set Block Neural Network is introduced to optimize the dynamic characteristic analysis model, and the intelligent model of model optimization analysis is established. Finally, the validity of the proposed algorithm is verified by simulation experiments of practical examples. [ABSTRACT FROM AUTHOR]

With the dramatic economic increases and irreversible increases of China's population, and declines of arable land, the feasible way to increase food production is to increase the grain yield per unit area. These result in the huge increases of nitrogen fertilizer application, and reducing nitrogen-use efficiency, lower economic profit, poor grain quality and environmental contamination by nitrogen. Selection of rice genotype with high nitrogen use efficiency is one feasible way of methods to improve nitrogen use efficiency. In this paper, we first introduce some operations on the intuitionistic fuzzy sets, and further develop the intuitionistic fuzzy Hamacher power weighted average (IFHPWA) operator. We also establish some desirable properties of this operator, such as idempotency, Boundedness and monotonicity. Then, we apply the intuitionistic fuzzy Hamacher power weighted average (IFHPWA) to deal with multiple attribute decision making with Intuitionistic fuzzy information. Finally, an illustrative example for Nitrogen use efficiency evaluation of different rice genotypes is given to verify the developed approach. [ABSTRACT FROM AUTHOR]

Unlike the other fuzzy neural networks, in this paper the fuzzy system and the neural network are separated, and they are corresponding to structure identification and parameter identification. The fuzzy model is generated automatically by on-line clustering method and fuzzy support vector machines. This fuzzy model is not updated, but its modeling error is compensated by a neural network. The neural network acts as the parameter identification model. The benefits of this new method are the structure is simple, and the physical meanings of each part of the model are clear. For the neural compensator, a new stable and fast training algorithm is proposed. Finally, this modeling method is successfully applied to model a magnetic tube recovery ratio in a metal company in China. [ABSTRACT FROM AUTHOR]