摘要
提出基于小波分析与神经网络的交通流短时预测方法,把多维输入进行小波分解降维,预测由多个子网络独立完成,有效解决了多维神经网络的映射学习容易产生"维数灾"的问题.示例结果表明,该方法比典型的神经网络预测准确度高、误差小.
The method based on wavelet analysis and neural network for short-term traffic flow forecasting is presented. The multidimensional inputs are decompounded by wavelet analysis and the forecasting is implemented by several sub neural networks independently. It resolves the dimension-disaster problem effectively in multidimensional neural network mapping. The demonstration results show that the method can evidently decrease prediction error and improve forecasting veracity compared with typical neural network.
出处
《信息与控制》
CSCD
北大核心
2007年第4期467-470,475,共5页
Information and Control
关键词
小波分析
小波神经元网络
交通流
短时预测
wavelet analysis
wavelet neural network
traffic .flow
short-term traffic prediction
