The Application of Support Vector Machine in Transformer Fault Diagnosis

Xiang Tan; Chang Shu; Yün Peng

doi:10.4028/www.scientific.net/amr.926-930.3410

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JOURNAL ARTICLE

The Application of Support Vector Machine in Transformer Fault Diagnosis

Xiang Tan Chang Shu Yün Peng

Year: 2014 Journal: Advanced materials research Vol: 926-930 Pages: 3410-3413 Publisher: Trans Tech Publications

DOI: 10.4028/www.scientific.net/amr.926-930.3410

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Abstract

The basic principle, training methods and model selection of support vector machine (SVM) are expounded in this paper, and then we introduce SVM in transformer fault diagnosis which can overcome the problems of the structure selection of neural network.

Keywords:

Support vector machine Transformer Artificial neural network Artificial intelligence Selection (genetic algorithm) Computer science Machine learning Engineering Fault (geology) Pattern recognition (psychology) Control engineering Electrical engineering Voltage

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Advanced Computational Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Sensor and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Decision-Making Techniques

Physical Sciences → Computer Science → Information Systems

The Application of Support Vector Machine in Transformer Fault Diagnosis

Abstract

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