基于门控递归单元神经网络的高速公路行程时间预测

刘松，彭勇，邵毅明，宋乾坤、LIU Song、Peng Yong、SHAO Yiming、SONG Qiankun

2019应用数学和力学Engineering被引 1开放获取

摘要

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.

引用本文（GB/T 7714）

刘松，彭勇，邵毅明，宋乾坤, LIU Song, Peng Yong, 等. 基于门控递归单元神经网络的高速公路行程时间预测[J]. 应用数学和力学, 2019.

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DOI：https://doi.org/10.21656/1000-0887.400187

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