LIU Song, PENG Yong, SHAO Yiming, SONG Qiankun. Expressway Travel Time Prediction Based on Gated Recurrent Unit Neural Networks[J]. Applied Mathematics and Mechanics, 2019, 40(11): 1289-1298. doi: 10.21656/1000-0887.400187
Citation: LIU Song, PENG Yong, SHAO Yiming, SONG Qiankun. Expressway Travel Time Prediction Based on Gated Recurrent Unit Neural Networks[J]. Applied Mathematics and Mechanics, 2019, 40(11): 1289-1298. doi: 10.21656/1000-0887.400187

Expressway Travel Time Prediction Based on Gated Recurrent Unit Neural Networks

doi: 10.21656/1000-0887.400187
  • Received Date: 2019-06-14
  • Rev Recd Date: 2019-07-19
  • Publish Date: 2019-11-01
  • To efficiently predict the travel time on the expressway, the travel time was studied with the gated recurrent neural network through collection of the swiping data of vehicles at toll gates on the expressway. By means of the developed prediction computer program, the effects of the proposed method were then tested with the charging data of the Guangzhou Airport south expressway. The results show that the prediction effects are satisfying. Comparison with the LSTM neural network and the BP neural network indicates that, the gated recurrent neural network is better in prediction accuracy.
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