摘要
介绍了目前国内外道路交通量预测的方法、特点及实际的预测效果。由于城市道路交通的复杂性,使得一些现有交通量预测方法的预测精度不高。针对这些问题,应用混沌神经网络,建立了城市道路交叉口出口交通量的浑沌神经网络预测模型,并与传统的BP神经网络预测结果对比,表明此模型具有较好的预测效果。
The methods, characters, and effect of urban road traffic volumes forecast at home a ld abroad were introduced. Because of the complexity of urban traffic, the prediction precision of some existing methods is not high. In this paper, the chaotic neural network was used to set up a model of traffic volume in real intersection exit. Through the comparison with the traditional BP neural network, the model has better effect in prediction.
出处
《交通与计算机》
2007年第6期28-30,33,共4页
Computer and Communications
基金
国家973计划项目资助(批准号:2006CB705500)
关键词
混沌神经网络
BP神经网络
建模
交通量
预测
chaotic neural networks
BP neural networks
modeling
traffic volume
forecast
