摘要 : Kernel Principal Component Analysis (KPCA) is an efficient multivariate statistical technique used for nonlinear process monitoring. Nevertheless, the conventional KPCA suffers high computational complexity in dealing with large s... 展开
作者 | Hajer Lahdhiri Ilyes Elaissi Okba Taouali Mohamed Faouzi Harakat Hassani Messaoud |
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作者单位 | |
期刊名称 | 《Stochastic environmental research and risk assessment》 |
页码/总页数 | 1833-1848 / 16 |
语种/中图分类号 | 英语 / P33 |
关键词 | Reduced Rank-KPCA Nonlinear process monitoring Fault detection |
DOI | 10.1007/s00477-017-1467-z |
馆藏号 | P-149 |