基于MATLAB神经网络工具箱的公交出行比例预测  

Forecasting the Proportion of Transit Trips Based on Neural Network Toolbox in MATLAB

作　　者：陈艳艳[1] 朱跃华[1] 王振报[2] 史建港[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 [2]河北工程大学土木工程学院,河北邯郸056038

出　　处：《北京工业大学学报》2008年第2期173-177,共5页Journal of Beijing University of Technology

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

摘　　要：在分析影响公交出行比例因素的基础上,运用城市已有的交通调查资料,建立了公交出行比例的BP神经网络预测模型,并利用MATLAB环境下的神经网络工具箱开发了相应程序.预测结果表明,该模型程序具有学习能力强、预测精度高、快速方便等特点,为公交出行比例的预测研究提供了一种可供借鉴的思路与方法,同时为用地规划、公交优先政策和需求管理政策的实施提供帮助.The author attempts to do research on effect factors related to proportion of transit trips first in this paper. BP neural network prediction model is established, based on available city traffic survey data. Mean-while, we develop corresponding programs by taking advantage of neural network toolbox in MATLAB. It is evident that it has characteristics of high learning capability, accurate prediction and convenience. And it provides a thinking and method of proportion of transit trips prediction research as a reference.

关 键 词：公交出行比例 BP模型 土地利用 预测 

分 类 号：U491[交通运输工程—交通运输规划与管理]