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小波神经网络在短时交通流预测中的应用
引用本文:孟杰,杨保成.小波神经网络在短时交通流预测中的应用[J].常熟理工学院学报,2012(4):83-86.
作者姓名:孟杰  杨保成
作者单位:常熟理工学院机械工程学院,江苏常熟215500
摘    要:研究了小波神经网络对于预测短时交通流的适应性,提出了利用小波神经网络的特性建立短时交通流预测模型;并利用苏州市某交叉口实测交通流量,运用小波神经网络建立了非线性回归预测模型,结果证明预测是可靠的,有助于城市交通流动态参数的预测,可为 ITS 的构建提供数据支持

关 键 词:交通流预测  短时交通流  小波神经网络  预测模型  非线性回归

A Forecasting Model for Short-term Traffic Flow Based on Wavelet Neural Networks
MENG Jie,YANG Bao-cheng.A Forecasting Model for Short-term Traffic Flow Based on Wavelet Neural Networks[J].Journal of Changshu Institute of Technology,2012(4):83-86.
Authors:MENG Jie  YANG Bao-cheng
Institution:(School of Mechanical Engineering,Changshu Institute of Technology,Changshu,215500,China)
Abstract:The research of short-term traffic flow is reviewed first.Based on analyzing the highly non-linear characteristic and researching the advantage of wavelet neural networks in handling non-linear and unsteady signal,the adaptive of wavelet neural networks on forecasting short-term traffic flow is researched and a forecasting model utilizing wavelet neural networks is put forward.Besides,through the practical flow data of a cross in the city of Suzhou,a nonlinear regressing model is built using wavelet neural networks.The result confirms the reliance and it can help the forecasting of urban dynamic flow,and it can also provide fundamental data for the intelligent traffic systems.
Keywords:traffic flow forecasting  short-term traffic flow  wavelet neural networks  forecasting model  non-linear regression
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