Combination of Multi-class Probability Support Vector Machines for Fault DiagnosisOA
Combination of Multi-class Probability Support Vector Machines for Fault Diagnosis
To deal with multi-source multi-class classification problems, the method of combining multiple multi-class probability support vector machines (MPSVMs) using Bayesian theory is proposed in this paper. The MPSVMs are designed…查看全部>>
To deal with multi-source multi-class classification problems, the method of combining multiple multi-class probability support vector machines (MPSVMs) using Bayesian theory is proposed in this paper. The MPSVMs are designed by mapping the output of standard support vector machines into a calibrated posterior probability by using a learned sigmoid function and then combining these learned binary-class probability SVMs. Two Bayes based methods for combining …查看全部>>
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Department of Automation, Shanghai Jiaotong Universtiy , Shanghai 200030;Department of Automation, Shanghai Jiaotong Universtiy , Shanghai 200030;Department of Automation, Shanghai Jiaotong Universtiy , Shanghai 200030;Department of Automation, Shanghai Jiaotong Universtiy , Shanghai 200030;Department of Automation, Shanghai Jiaotong Universtiy , Shanghai 200030
化学化工
support vector machinesdata fusionBayesian theoryfault diagnosis
support vector machinesdata fusionBayesian theoryfault diagnosis
《东华大学学报（英文版）》 2006 (1)
基于多信息融合的复杂工业过程广义知识模型与优化控制
12-17,6
This work was supported by the National Key Fundamental Research Project of China (2002cb312200), the National High Technology Research and Development Program of China (2002AA412010), and in part supported by the Natural Science Foundation of China (60575036).
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