Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021;
2021:3338840. [PMID:
34777491 PMCID:
PMC8589477 DOI:
10.1155/2021/3338840]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/22/2021] [Accepted: 10/22/2021] [Indexed: 11/18/2022]
Abstract
In recent years, more and more attention has been paid to the utilization of data and information in the logistics distribution path optimization system of e-commerce, but it is difficult to have scientific guarantee in the process of determining the optimal distribution path scheme of e-commerce. How to realize the optimization and adaptive setting of distribution path by using intelligent algorithm has become a hot spot. To battle these issues, this paper studies the logistics distribution path optimization model based on recursive fuzzy neural network algorithm. This paper analyses the research status of logistics distribution path determination scheme and applies the recursive fuzzy neural network algorithm in the selection of e-commerce logistics distribution path scheme. The experimental results show that the recursive fuzzy neural network algorithm can realize the optimization of e-commerce logistics distribution path, and the best distribution route can be made according to the characteristic difference of logistics distribution route, and its distribution accuracy can reach more than 97%.
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