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作者:

Zhao, Xiao-Hua (Zhao, Xiao-Hua.) | Tan, Ling-Long (Tan, Ling-Long.) | Hu, Dun-Li (Hu, Dun-Li.)

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摘要:

A new algorithm based on FCM, Sub_FCM is presented. This algorithm is combined with subtractive clustering and cluster validity evaluation. It can be used to determine the optimal cluster number and initialize clustering prototype automatically. An automatic classification model based on Alternative Optimization strategy and an unsupervised machine learning method are proposed. Experiments show that the internal structure of the traffic flow data is revealed correctly and the proper traffic flow range is determined automatically. The results lay the foundation for applying a proper control algorithm.

关键词:

Traffic surveys Learning systems Automatic programming Clustering algorithms

作者机构:

  • [ 1 ] [Zhao, Xiao-Hua]Key Lab. of Transportation in Beijing, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Tan, Ling-Long]School of Electromechanical Engineering, North China University of Technology, Beijing 100041, China
  • [ 3 ] [Hu, Dun-Li]School of Electromechanical Engineering, North China University of Technology, Beijing 100041, China

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2011

期: 8

卷: 37

页码: 1169-1174

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