基于GA-BP神经网络的南昌市农产品冷链物流需求预测分析

Prediction of Cold Chain Logistics Demand for Agricultural Products in Nanchang:An Analysis Based on GA-BP Neural Network

以冷链物流需求为研究对象,从冷链物流市场规模、交通运输能力、经济发展水平三大维度构建指标体系。利用遗传算法(GA)优化BP神经网络的权值和阈值,构建能够有效提升模型精度和稳健性的GA-BP神经网络预测模型,并使用此模型预测2023—2027年南昌市农产品冷链物流的需求量。结果表明,与BP神经网络模型比较,GA-BP神经网络模型准确率更高、收敛速度更快、稳定性更好。这为提升农产品冷链物流管理和运营效率提供了重要的参考依据。

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.