基于人工神经网络的商业网点交通方式研究  

Modal Split of Commercial Sites Based on Artificial Neural Network

作　　者：朱跃华[1] 陈艳艳[1] 耿雪[1] 柳丽娜[1] 

机构地区：[1]北京工业大学交通工程北京市重点实验室,北京100022

出　　处：《交通运输系统工程与信息》2008年第1期86-91,共6页Journal of Transportation Systems Engineering and Information Technology

基　　金：北京市教委重点项目(KZ200510005002);霍英东教育基金项目(104008)

摘　　要：针对商业网点的交通方式构成特性,首先分析了影响交通方式选择的因素,在北京市商业网点的调查数据基础上,利用人工神经网络强大的非线性映射能力和泛化功能,建立了公交出行比例预测的神经网络模型,并定量地分析了影响因素值的改变对公交比例的影响,预测了在不同策略下商业网点公交出行比例的变化情况.Aiming at features of traffic structure in commercial sites, the paper discusses the factors which effect the public traffic modal split. The BP neural network can approach continuous function precisely. So under the strong non-linear mapping and generalization characteristics of BP neural network, a prediction model of commercial sites have been established based on the available commercial sites survey data of Beijing. Meanwhile, this paper has developed the corresponding program taking advantage of the neural network toolbox in MATLAB. When the factors change, it can quantitatively analyze the influence to the proportion of transit trips.

关 键 词：BP神经网络 商业网点 交通方式 公交比例 

分 类 号：U491[交通运输工程—交通运输规划与管理]