Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics

In numerous industrial applications where safety, efficiency, and reliability are among primary concerns, condition-based maintenance (CBM) is often the most effective and reliable maintenance policy. Prognostics, as one of the key enablers of CBM, involves the core task of estimating the remaining...

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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 28; číslo 10; s. 2306 - 2318
Hlavní autoři:	Chong Zhang, Pin Lim, Qin, A. K., Kay Chen Tan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.10.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Artificial neural networks Belief networks Benchmark testing Deep belief network (DBN) Degradation ensemble learning Estimation evolutionary algorithm (EA) Evolutionary algorithms Industrial applications Maintenance engineering multiobjective Multiple objective analysis Neural networks Objective function prognostics Reliability Reliability aspects Training Useful life
ISSN:	2162-237X, 2162-2388
On-line přístup:	Získat plný text
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