This paper proposes a weighted C-SVM algorithm and analyzes its classification performance theoretically.

提出了一种加权C—SVM分类算法，并从理论上分析了算法的性能。

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Time series modeling and identification techniques were analyzed and the ARMA time series model based on robust LS-SVM algorithm was proposed.

对时序数据建模与辨识技术进行了分析，提出了使用鲁棒LS-SVM算法建立ARMA时序预测模型。

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Experiments are made on UCI database, and the results indicate the MBI-SVM algorithm has many good characteristics, such as stability, feasibility and practicality.

在UCI数据库上进行了实验，结果证实该算法具有较高的稳定性、可行性和实用性。

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