A SUPPORT VECTOR MACHINE WITH THE TABU SEARCH ALGORITHM FOR FREEWAY INCIDENT DETECTION

被引：60
|
作者：
Yao, Baozhen [1 ]
Hu, Ping [1 ]
Zhang, Mingheng [1 ]
Jin, Maoqing [2 ]
机构：
[1] Dalian Univ Technol, Sch Automot Engn, Dalian 116024, Peoples R China
[2] Minist Sci & Technol, High Technol Res & Dev Ctr, Beijing, Peoples R China
来源：
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE | 2014年 / 24卷 / 02期
基金：
中国国家自然科学基金; 美国国家科学基金会;
关键词：
automated incident detection; support vector machine; tabu search; freeway; TIME PREDICTION; NEURAL-NETWORK; CLASSIFICATION; OPTIMIZATION; SELECTION; STRATEGY; MODELS; SVM;
D O I：
10.2478/amcs-2014-0030
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：397 / 404
页数：8
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