Application of Combined Model in Forecasting Logistic Volume of A Port

摘要：

Firstly, this paper predicts the volume of logistics in Ningbo Port with the two methods of improved BP neural network and gray model, and introduces combined forecast methods on the basic of researching on those two forecast methods. Theories and practices have shown that combined forecast model are more accurate than single forecast model, and can enhance the stability of the forecast, thus own higher ability to predict environmental change. Based on the Shapley value allocation of the combined forecast model, this paper aims to study the demand forecast of the logistics. The two methods mentioned inferior are realized by matlab programming.

关键词： loglstlcs volume of a port BP neural network gray model combined forecast model

作者: Peihua Fu Yajie Li

作者单位: College of Computer and Information Engineering Zhejiang Gongshang University Hangzhou,China College of Computer and Information Engineering Zhejiang Gongshang University Hangzhou, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 742-745

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）