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模拟电路故障的支持向量机集成诊断新方法

更新时间:2020-10-18 23:05:50 大小:309K 上传用户:zhengdai查看TA发布的资源 标签:模拟电路 下载积分:1分 评价赚积分 (如何评价?) 打赏 收藏 评论(0) 举报

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为了解决支持向量机应用于多类别模拟故障诊断时泛化性能较低导致诊断精度难以提高的问题,提出了一种基于支持向量机集成的模拟电路故障诊断新方法.首先,通过将本次迭代中不可分区域的样本加入训练集来构造下一次迭代的训练集,以提高基分类器间的差异性;然后选择分类精度不低于平均分类精度的基分类器进行集成,以提高整体诊断精度.实验表明,该方法应用于线性及非线性模拟电路均取得了良好的诊断效果.

In order to solve the problem of improving the generalization performance and diagnosis precision when support vector machine is applied to multi-class analog fault diagnosis,a novel method of analog circuit fault diagnosis based on support vector machine ensemble was st,the unclassifiable samples of the iteration was added to training sample set to constitute the training sample set of next iteration,and the diversified classifiers were then,the classifiers whose accuracy are not less than the average accuracy were selected to ensemble,and the overall diagnostic accuracy was experiment results show that the proposed strategy is applicable to both linear and nonlinear analog circuits fault diagnosis.

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模拟电路故障的支持向量机集成诊断新方法.pdf 309K

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