Research on demand prediction of cold chain logistics for fresh agricultural products in Anhui Province
The demand for fresh agricultural products and other cold chain products in the market is rapidly increasing,but the supply of cold chain logistics cannot meet people's needs,bring new challenges to fresh agricultural products.As a region rich in agricultural products,the supply of fresh agricultural products in Anhui Province is crucial for meeting market demand.Therefore,this paper collected fresh agricultural product yield data from 2001 to 2022 and trained and validated three models:back propagation neural network(BP neural network),long short term memory(LSTM),and particle swarm optimization long short term memory(PSO-LSTM).Through comparative analysis of the three models,the relative errors of the three models were 0.13%,0.06%,and 0.02%,respectively.The results showed that the PSO-LSTM model has the highest prediction accuracy and the best fitting effect,and can effectively predict the cold chain logistics demand for fresh agricultural products in Anhui Province in the next four years to cope with the growing pressure of cold chain logistics demand.
万方数据
维普
