山东科学2012，Vol.25Issue(3)：23-28,6.
基于RBF神经网络的城市快速路短时交通流预测研究
RBF neural network based urban expressway short-term traffic flow prediction
摘要
Abstract
We analyzed and compared the effects of gray model GM （1 ,1） and RBF neural network model on short-term traffic flow prediction to test their feasibility and applicability. Practical instances show that gray model is inapplicable to the short-term prediction of traffic flow, but RBF neural network model is applicable. Moreover, we can acquire higher prediction accuracy when the distribution density of the radial basis function is from 0.8 to 1. 0.关键词
交通流/预测/灰色模型/RBF神经网络Key words
traffic flow/prediction/gray model/RBF neural network分类
交通工程引用本文复制引用
郑宣传,韩宝明,李得伟..基于RBF神经网络的城市快速路短时交通流预测研究[J].山东科学,2012,25(3):23-28,6.基金项目
国家科技支撑计划项目 （）
国家自然科学基金 （）
