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Issue title: Fuzzy model for human autonomous computing in extreme surveillance and it’s applications
Guest editors: Varatharajan Ramachandran
Article type: Research Article
Authors: Yaxu, Yang; *
Affiliations: Hebei University, Baoding, China
Correspondence: [*] Corresponding author. Yang Yaxu, Hebei University, Baoding, China. E-mail: yyx921109@163.com.
Abstract: The loose logistics market, the weak value-added service capabilities of enterprises, and the backward construction and operation of logistics networks have led to high logistics costs and low efficiency in some enterprises. In order to improve the comprehensive evaluation effect of enterprise logistics enterprise competitiveness, this paper builds a comprehensive evaluation model of logistics enterprise competitiveness based on SEM model based on machine learning technology. Moreover, in order to more accurately grasp the law of customer logistics mode selection behavior, this paper adds the adaptive value of the latent variables of the logistics mode service characteristics obtained through the SEM model to the utility function of the logistics mode to obtain the SEM-NL integrated model. In addition, starting from the analysis of the key factors affecting the competitiveness of enterprise logistics, this paper constructs an evaluation model of enterprise logistics competitiveness, and analyzes and studies the comprehensive competitiveness of enterprise logistics through two aspects of logistics actual competitiveness and logistics future development potential. The research results show that the model constructed in this paper is suitable for the comprehensive evaluation of the competitiveness of logistics enterprises.
Keywords: SEM model, logistics enterprise, competitiveness, comprehensive evaluation
DOI: 10.3233/JIFS-189486
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6469-6479, 2021
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