A belief function theory based approach to combining different representation of uncertainty in prognostics

Information Sciences

Volumn 303, Issue , 2015, Pages 134-149

  Baraldi, Piero ^a   Mangili, Francesca ^b   Zio, Enrico ^a,c  

^a POLITECNICO DI MILANO   (Italy)

^b DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE IDSIA   (Switzerland)

^c ECOLE CENTRALE PARIS   (France)

Author keywords

Belief function theory; Filter clogging; Gaussian process regression; Prognostics; Uncertainty representation

Indexed keywords

BOILING WATER REACTORS; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); NUCLEAR FUELS; NUCLEAR POWER PLANTS; SEAWATER; UNCERTAINTY ANALYSIS;

BELIEF FUNCTION THEORY; FILTER CLOGGING; GAUSSIAN PROCESS REGRESSION; PROGNOSTICS; UNCERTAINTY REPRESENTATION;

PROBABILITY DENSITY FUNCTION;

EID: 84925678190     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.12.051     Document Type: Article

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