文献类型：会议论文

英文题名：Building logistics cost forecast based on high speed and precise genetic algorithm neural network

作者：Gao, Meijuan[1]; Tian, Jingwen[1]; Xu, Jin[2]

第一作者：高美娟

通讯作者：Gao, M.

机构：[1] College of Automation, Beijing Union University, Beijing, China; [2] School of Information Science, Beijing University of Chemical Technology, Beijing, 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]College of Automation, Beijing Union University, Beijing, 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：2009 International Workshop on Intelligent Systems and Applications, ISA 2009

会议日期：May 23, 2009 - May 24, 2009

会议地点：Wuhan, China

语种：英文

外文关键词：Buildings - Digital arithmetic - Forecasting - Genetic algorithms - Intelligent systems - Neural networks - Speed

摘要：The building logistics cost forecasting was a complicated nonlinear problem, due to the factors that influence building logistics cost are anfratuous, and it was difficult to describe it by traditional methods. So a modeling and forecasting method of building logistics cost based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We constructed the network structure, and discussed and analyzed the effect factor of building logistics cost. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, 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. ? 2009 IEEE.