基于RBF网络的道路交通能力预测  

The traffic capacity prediction based on RBF network

作　　者：袁立行[1] 王玲芝[1] 

机构地区：[1]西安邮电学院自动化学院,陕西西安710121

出　　处：《西安邮电学院学报》2011年第2期42-45,共4页Journal of Xi'an Institute of Posts and Telecommunications

摘　　要：交通系统是一个复杂的非线性不确定动态系统,难以利用精确的数学模型来表达。针对此问题提出一种径向基函数(Radial Basis Function,RBF)网络方法,对交通运输量进行预测研究。分别取当地生产总值GDP、工业总产值及铁路运输线路长度等8项指标作为货运量的影响因子,以货运总量、铁路货运量和公路货运量作为货运量的输出因子,即网络的输出。仿真结果显示,基于RBF网络测试的道路交通能力测试误差较小,预测精度较高,说明RBF网络在货运量预测方面具有有效性。Traffic System is a complex,nonlinear and uncertain dynamic one,which is hard to describe through accurate mathematics mode.A method based on RBF（Radial Basis Function） network is proposed here,which is used for predicting traffic transportation.Eight indexes such as local GDP,total industrial output value and the length of railway transportation line are taken as the influence factors,while,the total freight transportation,the railway transportation and the highway transportation are taken as the output factors,which is the output of the network.Simulation results show that the testing error of the traffic capacity based on RBF network is smaller,and the prediction precision is higher.The validity of RBF network in freight transportation prediction is also proved.

关 键 词：径向基网络 交通系统 能力预测 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]