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- W2366279269 abstract "The transformer is an important electric equipment in the power system,whose running state plays an important role in the safe operation of the system.This paper introduced thecost-sensitive learning mechanism to the Relevance Vector Machine,and put forward the term:the Cost-Sensitive Relevance Vector Machine(CS-RVM).With the minimum misdiagnosis loss cost as the goal,the algorithm predicted the fault categories of new samplesaccording to the Bayesian risk theory.With typical examples the paper verified the CS-RVM had high diagnostic accuracy,and could to some extent avoid the misdiagnosis of faultor misdiagnosing high-risk failure as low risk failure.On this basis,the paper tried to apply the CS-RVM to the insulation condition assessment of the transformerproposed the fault diagnosis method of the oil-immersed power transformer based on the CS-RVM so as to overcome the problem that the existing transformer fault diagnosis method did not take into account the issue of misdiagnosis cost difference,and finally verified the effectiveness of the proposed diagnostic method by means of the transformer fault diagnosis example based on the DGA data." @default.
- W2366279269 created "2016-06-24" @default.
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- W2366279269 date "2014-01-01" @default.
- W2366279269 modified "2023-09-28" @default.
- W2366279269 title "Insulation Condition Assessment of the Transformer Based on the Cost-Sensitive Relevance Vector Machine" @default.
- W2366279269 hasPublicationYear "2014" @default.
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