A New Algorithm of Support Vector Machine Ensemble and Its Application

摘要：

A new ensemble algorithm for support vector machine (SVM) based on attributes reduction and parameters disturbance is proposed, which is applied to analog circuit fault diagnosis. Firstly, the feature space is divided in sevaral subspaces by attributes reduction alogrithm with assurance of high classification capability. And then, for each subspace, the model parameters are disturbed in lowbias region. The final result is obtained by using the majority voting procedure twice. Take Sallen-key band-pass filter as simulation instance, and the fault diagnosis result indicates that the algorithm presented in the paper has bettter performance then single SVM, Adaboost algorithm, Attribute Bagging algorithm and so on.

关键词： Attributes Reduction Parameters Disturbance SVM Ensemble Algorithm Analog Circuit Fault Diagnosis

作者: MA Chao CHEN Xihong

作者单位: Missile institute Air Force Engineering University Shanxi Sanyuan,China

会议类型: 国际会议

会议名称: 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

会议地点: 南京

会议语种:英文

页码: 225-229

在线出版日期: 2010-08-26（万方平台首次上网日期，不代表论文的发表时间）