基于BP神经网络的物流需求量预测模型研究

Research on Forecasting Model of Logistics Demand Based on BP Neural Network

本文利用神经网络理论,建立了时间序列对象的反向传播(back-propagation,BP)预测模型,运用于物流需求量预测,并通过实例分析,验证了本模型的科学性与正确性。

This paper constructs the forecasting model of back-propagation using the theory of neural network, applying it to the logistics demand forecast, and validates its correctness and rationality by analyzing examples.