关键词: 支持向量机, 参数优选, 实数量子进化算法, 交通流预测

Abstract: Support Vector Regression（SVR） based on statistical learning theory and structural risk minimization principle is a powerful tool for solving small-sample regression problem，and selecting appropriate parameters is very crucial to learn accuracy and generalization performance of SVR.Firstly，the parameters selection of SVR is considered as a combinatorial optimization problem，and the objective function of optimization problem is set.Then，Real-coded Quantum Evolutionary Algorithm（RQEA） is employed to solve this problem furthermore to select appropriate parameters of SVR，which is called RQEA-SVR，and RQEA-SVR is applied to the problem of traffic flow forecasting.The experiment results show that the proposed method is an effective approach for parameters selection of SVR，and the good performance for traffic flow forecasting is obtained.

Key words: Support Vector Regression（SVR）, parameters selection, real-coded quantum evolutionary algorithm, traffic flow forecasting