中国机械工程2011，Vol.22Issue(1)：80-83,4.
主成分分析法与核主成分分析法在机械噪声数据降维中的应用比较
Comparison between PCA and KPCA Method in Dimensional Reduction of Mechanical Noise Data
摘要
Abstract
According to the classification principle of linear and non-linear dimensional reduction,this paper dealt with mechanical noise data under different working-modes through PCA and KPCA. Lastly,the paper computed the right recognition percentage of noise data, including had been reduced and not, by NN method and SVM method, and compared the excellence for PCA and KPCA in dimensional reduction. Consequently, a better method of dimensional reduction is selected for ribbed cylindrical double-shells according to the results.关键词
主成分分析法/核主成分分析法/核函数/神经网络/支持向量机/机械噪声/降维分类
通用工业技术引用本文复制引用
梁胜杰,张志华,崔立林..主成分分析法与核主成分分析法在机械噪声数据降维中的应用比较[J].中国机械工程,2011,22(1):80-83,4.基金项目
国家自然科学基金资助项目(50775218) （50775218）
