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Issue title: Special Section: Big data analysis techniques for intelligent systems
Guest editors: Ahmed Farouk and Dou Zhen
Article type: Research Article
Authors: Yuan, Qingwen; *
Affiliations: Department of Finance and Economics, Shandong University of Science and Technology, Jinan, China
Correspondence: [*] Corresponding author. Qingwen Yuan, Department of Finance and Economics, Shandong University of Science and Technology, Jinan, 250031, China. E-mail: Tiger_yuan@163.com.
Abstract: Cross border logistics and cross-border e-commerce are complementary relations. On the one hand, cross-border logistics has promoted the development of cross-border e-commerce. On the other hand, the development of cross-border e-commerce brings more opportunities for the construction of cross-border logistics. With the continuous progress and innovation of technology, the new technology represented by AI (Artificial Intelligence) is relatively mature. The application of intelligent logistics system in cross border e-commerce logistics industry will become the trend of international logistics development. Based on this, the construction mechanism and algorithm of cross-border e-commerce export logistics mode are analyzed from the perspective of value chain. From the perspective of value chain, a BP neural network model based on logistics distribution center location is established to perfect the mechanism of cross-border e-commerce export logistics. Finally, the particle swarm optimization and the ant colony algorithm and the ELECTRE-II algorithm are proposed, with the effectiveness of this algorithm verified. The results prove the effectiveness of the proposed algorithm.
Keywords: Algorithm, value chain, export logistics mode, construction mechanism
DOI: 10.3233/JIFS-179142
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3393-3400, 2019
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