Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm

• Published in: Computational intelligence and neuroscience Vol. 2021; no. 1; p. 3338840
• Main Author: Liu, Binbin
• Format: Journal Article
• Language: English
• Published: United States Hindawi 2021; John Wiley & Sons, Inc
• Subjects: Algorithms; Analysis; Artificial neural networks; Cloud computing; Commerce; Data analysis; Data mining; Efficiency; Electronic commerce; Experiments; Fuzzy logic; Logistics; Neural networks; Neural Networks, Computer; Optimization models; R&D; Research & development; Route optimization; Sawmills
• ISSN: 1687-5265; 1687-5273; 1687-5273
• DOI: 10.1155/2021/3338840

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%.