Abstract:Abstract.A large amount of real-time traffic data supports the processing requirements of traffic state discrimination and prediction. Therefore, accurate real-time traffic information can be grasped for effective detection of outliers. In this paper, an optimized AdaBoost model for screening abnormal traffic samples is proposed based on the multi-source features of the detected data. Considering the unbalanced characteristics of traffic data, AdaBoost is optimized by cost-sensitive method, which avoids the pr… Show more
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