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Supply Chain Collaboration Degree of Manufacturing Enterprises Using Matter-Element Method
( Qiang Xiao ),( Shuangshuang Yao ),( Mengjun Qiang ) 한국정보처리학회 2021 Journal of information processing systems Vol.17 No.5
Evaluation of the collaboration of the upstream and downstream enterprises in the manufacturing supply chain is important to improve their synergistic effect. From the supply chain perspective, this study establishes the evaluation model of the manufacturing enterprise collaboration on the basis of fuzzy entropy according to synergistic theory. Downstream enterprises carry out coordinated capital, business, and information flows as subsystems and research enterprises as composite systems. From the three subsystems, the collaboration evaluation index is selected as the order parameter. The compound fuzzy matter-element matrix is established by using its improved algorithm. Subordinate membership and standard deviation fuzzy matter-element matrixes are constructed. Index weight is determined using the entropy weight method. The closeness of each matter element is then calculated. Through a representative of the home appliance industry, namely, Gree Electric Appliances Inc. of Zhuhai, empirical analysis of data in 2011-2017 from the company and its upstream and downstream enterprise collaboration shows a good trend, but the coordinated development has not reached stability. Gree Electric Appliances Inc. of Zhuhai need to strengthen the synergy with upstream and downstream enterprises in terms of cash, business, and information flows to enhance competitiveness. Experimental results show that this method can provide precise suggestions for enterprises, improve the degree of collaboration, and accelerate the development and upgrading of the manufacturing industry.
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Health Status Evaluation of Catenary Based on Normal Fuzzy Matter-Element and Game Theory
Lingzhi Yi,Jian Zhao,Wenxin Yu,Guzong Long,Haoyi Sun,Wang Li 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.5
At present, there is no unifi ed standard for the health status evaluation of electrifi ed railway catenary in China. The current catenary evaluation model only considers quantitative detection indicators, without qualitative indicators such as weather, which is one-sided to some extent. Thus, an improved catenary status evaluation model is constructed with both quantitative indicators and qualitative indicators. In this evaluation model, the normal fuzzy matter-element method is used to determine the correlation value of each grade, and the weighted average principle is used to re-determine the status grade of catenary when the maximum correlation principle fails. Meanwhile, entropy weight method and particle swarm optimization algorithm to optimize analytic hierarchy process method are combined to improve the shortcomings of single weight method, and game theory is used to determine the subjective and objective weight coeffi cients, so as to reduce the infl uence of subjective experience. Select a Chinese railway catenary in 2018 as an example for verifi cation analysis, the results show that the model constructed in this paper can eff ectively help professionals to make correct judgments on the health status of catenary, and provide a new idea and method for the comprehensive evaluation of the catenary operation status, which has certain practicability
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