Fault detection based on a robust one class support vector machine

Neurocomputing

Volumn 145, Issue , 2014, Pages 263-268

  Yin, Shen ^a,b   Zhu, Xiangping ^a   Jing, Chen ^a  

^a BOHAI UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Fault detection; One class support vector machines; Outliers; Support vector machines

Indexed keywords

FAULT DETECTION; STATISTICS;

ANOMALY DETECTION; FAULT DETECTION SCHEMES; GENERAL SUPPORTS; ONE-CLASS SUPPORT VECTOR MACHINE; OUTLIERS; PENALTY FACTOR; SIMULATION EXAMPLE; TRAINING DATA SETS;

SUPPORT VECTOR MACHINES;

ARTICLE; FAULT DETECTION; INTERMETHOD COMPARISON; KERNEL METHOD; MATHEMATICAL MODEL; ONE CLASS SUPPORT VECTOR MACHINE; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; PROCESS TECHNOLOGY; SIMULATION; SUPPORT VECTOR MACHINE; VALIDATION PROCESS;

EID: 84906939980     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.05.035     Document Type: Article

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