Study on application of multi-kernel learning relevance vector machines in fault diagnosis of power transformers

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 33, Issue 22, 2013, Pages 68-74

  Zhu, Yongli ^a   Yin, Jinliang ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Fault diagnosis; Informative integration; Multi kernel learning (MKL); Parameters optimization; Power transformers; Relevance vector machine (RVM)

Indexed keywords

FAILURE ANALYSIS; NEURAL NETWORKS; OPTIMIZATION; SUPPORT VECTOR MACHINES;

BACK-PROPAGATION NEURAL NETWORKS; HETEROGENEOUS SOURCES; KERNEL FUNCTION PARAMETERS; MULTI-KERNEL LEARNING; PARAMETERS OPTIMIZATION; POWER TRANSFORMER FAULT DIAGNOSIS; RELEVANCE VECTOR MACHINE; TRANSFORMER FAULT DIAGNOSIS;

POWER TRANSFORMERS;

EID: 84881652320     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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