Prediction of Yangtze River Containerized Freight Index Based on PSO-RBF Combined Model
Yangtze River containerized freight index,as a barometer of the Yangtze River shipping market,can effectively reflect the economic situation of China's Yangtze River shipping and reflect the development dynamics of China′s inland waterway shipping.The forecast of Yangtze River containerized freight index can provide important basis for the management decision of coastal shipping enterprises and the government′s macroeconomic formulation.Eight indexes affecting the Yangtze River contain-erized freight index were selected,BP neural network and RBF neural network were used to forecast the Yangtze River container-ized freight index from 2017 to May 2022,and an improved PSO-RBF combination model was proposed,which obtained a small prediction error.The results showed that the particle swarm optimization algorithm can optimize the key parameters of the RBF neural network,such as the output weight and the hidden cell center,so that the RBF neural network can converge better,and the results are better than other algorithms.The results showed that PSO-RBF combination model is an effective method to pre-dict the Yangtze River containerized freight index.
Yangtze River containerized freight indexparticle swarm optimizationRBF neural networkcombination mod-elprediction
NETL
NSTL
万方数据
维普
