A Neural Networks Ensemble Based Demand Forecasting Model for Third-party Logistics

摘要：

A neural networks ensemble based demand forecasting model for third-party logistics was proposed to solve the problems of nonlinearity, variation, small sample size and large deviation in predicting logistics demand of 3PL companies. At first, an analysis of logistics demand was conducted and six input indicators were chosen. And then, the concept of neural networks ensemble was introduced and its generalization performance was analyzed. And detailed steps of implementation were proposed.At last, experiments based on technique of bagging ensemble were conducted to prove that the proposed model was feasible.

关键词： logistics demand forecasting neural networks ensemble third-party logistics bagging generalization performance

作者: Peng Minjing

作者单位: School of Business Administration South China University of Technology,Guangzhou,Guangdong,P.R.China,510641;School of Management Wuyi University,Jiangmen,Guangdong,P.R.China,529020

会议类型: 国际会议

会议名称: 2006 International Conference on Management Science and Engineering(2006管理科学与工程国际学术研讨会)

会议地点: 武汉

会议语种:英文

页码: 1095-1099

在线出版日期: 2006-11-08（万方平台首次上网日期，不代表论文的发表时间）