Prediction of Cold Chain Logistics Demand for Agricultural Products in Nanchang:An Analysis Based on GA-BP Neural Network
Taking the demand for cold chain logistics as the research object,an indicator system is constructed from the dimensions of logistics market size,transport capacity and economic development level.By using genetic algorithm(GA)to optimize the weights and thresholds of the neural network,a GA-BP neural network prediction model that can effectively improve the accuracy and robustness is formed.And the model is used to predict the demand for agricultural products in Nanchang from 2023 to 2027.The results show that compared with the BP neural network model,the GA-BP neural network model has higher accuracy,faster convergence speed and better stability.This provides important reference for improving the management and operational efficiency of cold chain logistics for agricultural products.
万方数据
维普
