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A support vector machine with the tabu search algorithm for freeway incident detection

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Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.
Rocznik
Strony
397--404
Opis fizyczny
Bibliogr. 38 poz., rys., tab., wykr.
Twórcy
autor
  • School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China
autor
  • School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China
autor
  • School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China
autor
  • High Technology Research and Development Center, Ministry of Science and Technology, Beijing, PR China
Bibliografia
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  • [5] Chen, S. and Wang, W. (2009). Decision tree learning for freeway automatic incident detection, Expert Systems with Applications 36(2): 4101–4105.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cf0b3eab-1ac9-48a8-9437-cffa03bec228
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