关键词: 交通流, 异常数据, 支持向量机, 最小二乘法

Abstract: Focusing on the phenomenon that the real traffic databases are highly susceptible to noisy, missing, and inconsistent data, a model is built based on least square Support Vector Machine（SVM） to detect the traffic abnormal data. It transforms the time series data into vector data with the method of phase-space reconstruction. Based on the SVM, it establishes the regression analyse model with the training data before distinguishing abnormal data by calculating the residual error between actual value and predictive value. With the empirical research in Bei Er Duan of the First Circle Road of Chengdu and the comparative analysis with the traditional detection method, the results prove the effectiveness of the proposed detection method.

Key words: traffic flow, discrepant data, support vector machine, least square