Research on Dynamic Path Planning of Cold Chain Logistics Based on Bp Neural Network Optimization

Abstract

With the development of information technology and computer technology, the research of automation and intellectualization in navigation has become a new research direction for marine scientists and technicians. The main research content of this paper is to apply genetic algorithm to automatic collision avoidance decision of ships, making use of the decision system to help the driver find a safe, effective and economical way to avoid the ship when the ship comes to ship. In this paper, the principle and mechanism of BP neural network are introduced, and the structure and algorithm of BP network are discussed, and the further optimization method is put forward, and the research results about the number of hidden layers, the selection of the number of nodes, the training of the form of error and the introduction of relearning strategy are given. Next, this paper discusses the development status of cold chain logistics in China, and the problems and countermeasures that the development of marine cold chain transportation faces. Finally, this paper focuses on the research on the decision making of collision avoidance action of ships, and gives a detailed discussion on the dynamic planning of marine cold chain route based on the BP neural network optimization.