Traditional Support Vector Machine(SVM), which based on batch training, can't satisfy the real-time requirement of environmental pollution prediction with large scale data. With the analysis of a typical kind of online support vector regression algorithm, this paper indicates that repeated sample move exists in the training process would lead to decrease the training speed, and proposes an improved algorithm. Simulation and analysis results show that the proposed algorithm performs high modeling precision, and training speed is increased remarkably compared with the aforementioned algorithm.%传统支持向量机基于批量训练方法,无法适应环境污染预测中的海量数据与实时性要求.在分析研究一种典型的在线支持向量机回归算法[4]的基础上,指出原算法在训练过程中存在样本重复移动问题,导致模型训练速度下降.提出一种改进算法,消除霹复移动问题.实验结果表明,该改进在线支持向量机算法建模精度高,训练速度较原算法有显著提高.
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