A new multivariate approach for prognostics based on extreme learning machine and fuzzy clustering

IEEE Transactions on Cybernetics

Volumn 45, Issue 12, 2015, Pages 2626-2639

  Javed, Kamran ^a   Gouriveau, Rafael ^a   Zerhouni, Noureddine ^a  

^a FEMTO ST INSTITUTE   (France)

Author keywords

Data driven; extreme learning machine (ELM); fuzzy clustering; prognostics; remaining useful life (RUL)

Indexed keywords

CONDITION MONITORING; FUZZY CLUSTERING; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; MACHINERY; NASA; PATIENT MONITORING; STATE ESTIMATION; TURBOFAN ENGINES;

CONDITION-MONITORING DATA; DATA-DRIVEN PROGNOSTICS; DISCRETE STATE ESTIMATION; DYNAMIC ENVIRONMENTS; EXTREME LEARNING MACHINE; MULTIVARIATE APPROACH; PROGNOSTICS AND HEALTH MANAGEMENTS; REMAINING USEFUL LIVES;

SYSTEMS ENGINEERING;

ALGORITHM; CLUSTER ANALYSIS; ENGINEERING; FUZZY LOGIC; MACHINE LEARNING; MULTIVARIATE ANALYSIS; THEORETICAL MODEL;

ALGORITHMS; CLUSTER ANALYSIS; ENGINEERING; FUZZY LOGIC; MACHINE LEARNING; MODELS, THEORETICAL; MULTIVARIATE ANALYSIS;

EID: 84960129882     PISSN: 21682267     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCYB.2014.2378056     Document Type: Article

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