文献类型：会议论文

英文题名：Building Logistics Cost Forecast Based on Wavelet Neural Network

作者：Gao, Meijuan[1];Feng, Qian[2];Tian, Jingwen[1]

第一作者：高美娟

通讯作者：Gao, MJ[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China;[2]Beijing Jiaotong Univ, Sch Econ & Management, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：International Conference on MultiMedia and Information Technology

会议日期：DEC 30-31, 2008

会议地点：Three Gorges, PEOPLES R CHINA

语种：英文

外文关键词：building logistics; logistics cost; forecast; wavelet neural network

摘要：The building logistics cost forecasting was a complicated nonlinear problem, due to the factors that influence building logistics cost are anfratuous, so it was difficult to describe it by traditional methods. The wavelet neural network (WNN) has the advantages of both wavelet analysis and neural network, in this paper, a modeling and forecasting method of building logistics cost based on WNN is presented. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network in a large extent. We discussed and analyzed the effect factor of building logistics cost. With the ability of strong nonlinear function approach and fast convergence rate of WNN, the modeling and forecasting method can truly forecast the building logistics cost by learning the index information. The actual forecasting results show that this method is feasible and effective.