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《Journal of Hunan University(Natural Sciences)》 2014-01
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A Travel Time Prediction Model Based on Traffic Data Fusion Technology

LI Jia;LIU Chun-hua;HU Sai-yang;WANG Fang;College of Civil Engineering,Hunan Univ;Fuzhou Survey Design Research Institute of China Civil Engineering Group;Vocational and Technical College of Qingyuan;  
The forecast of the current urban road travel time is mostly limited to single-source data and the prediction accuracy is not high.Based on the floating car GPS data and microwave detector traffic data,a model of travel time was built in the fusion method.Wavelet neural network was optimized by using genetic algorithms,which can solve the blindness and the randomness of selecting wavelet neural network initial parameter,thus greatly improving Web search efficiency and the speed of training.The predicted travel time is in good agreement with video observed data.The results show that the model is effective and reliable.
【Fund】: 广东省低碳发展专项资金项目(粤发改资环[2011]1273号-19)
【CateGory Index】: U491.14
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