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

• Autorzy: Baozhen Yao , Ping Hu , Mingheng Zhang , Maoqing Jin
• 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.

Słowa kluczowe

EN

automated incident detection; support vector machine; tabu search; freeway

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2014
• Tom: 24
• Numer: 2
• Strony: 397-404

Daty

wydano

2014

otrzymano

2013-07-18

poprawiono

2013-10-30

Twórcy

autor

Baozhen Yao

• School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China

autor

Ping Hu

• School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China

autor

Mingheng Zhang

• School of Automotive Engineering, Dalian University of Technology, Dalian 116024, PR China

autor

Maoqing Jin

• High Technology Research and Development Center, Ministry of Science and Technology, Beijing, PR China

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Identyfikatory

DOI

10.2478/amcs-2014-0030