LSTM和GRU模型对湖北省物流需求预测性能比较研究  

Comparative Study of LSTM and GRU Models on the Prediction Performance of Logistic Demand in Hubei Province

作　　者：王泽宇 张志清[1] WANG Ze-yu;ZHANG Zhi-qing(Wuhan University of Science and Technology,Wuhan 430065,China)

机构地区：[1]武汉科技大学,湖北武汉430065

出　　处：《物流工程与管理》2024年第4期10-14,共5页Logistics Engineering and Management

摘　　要：预测物流需求是提高和优化物流供应链效率和降低成本的关键因素。文中以湖北省物流需求为应用场景,采用LSTM和GRU网络对湖北省物流需求量进行预测,根据误差对比发现,LSTM网络的性能显著优于GRU网络,拥有更高的预测精度。Predicting logistics demand is a key factor in improving and optimizing logistics supply chain efficiency and reducing costs.This paper takes the logistics demand of Hubei Province as the application scenario,and uses LSTM and GRU networks to predict its logistics demand.According to the error comparison,it is found that the performance of LSTM network is significantly better than that of GRU network,and it has higher prediction accuracy.

关 键 词：物流预测 LSTM网络 GRU网络 

分 类 号：F259.27[经济管理—国民经济]