• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 20 Issue 6
Dec.  2007
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Article Contents
LI Ruimin, LU Huapu, SHI Qixin. ANN-Based Prediction of Turning Rate of Traffic Flows at Intersection[J]. Journal of Southwest Jiaotong University, 2007, 20(6): 743-747.
Citation: LI Ruimin, LU Huapu, SHI Qixin. ANN-Based Prediction of Turning Rate of Traffic Flows at Intersection[J]. Journal of Southwest Jiaotong University, 2007, 20(6): 743-747.

ANN-Based Prediction of Turning Rate of Traffic Flows at Intersection

  • Received Date: 28 Jun 2006
  • Publish Date: 25 Dec 2007
  • Based on an improved back-propagation neural network,a predication model for the turning rate of traffic flows at intersections was proposed to predict traffic flows for the signal control of intersections.The corresponding method to determine necessary parameters in this model was given.To improve the learning rate and reliability of neural network algorithms,the self-adaptive learning rate approach and the gradient descent with momentum method were adopted.In addition,a simulation was carried out to prove the correctness of the proposed model.The research result shows that compared with the average value method,the proposed model can decrease the mean absolute relative error by 1%~3%.

     

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