Affiliation:
1. Hebei University of Engineering
Abstract
Support vector machine (SVM) is a novel machine learning method based on statistical learning theory. SVM is powerful for the problem with small sampling, nonlinear and high dimension. A decision directed acyclic graph(DDAG) based on SVM classifier is applied to fault diagnosis of power transformer. We optimize the structure of a decision directed acyclic graph by putting SVM with higher generalization ability at the upper nodes of the decision tree. The test results show that the classifier has an excellent performance on training speed and reliability.
Publisher
Trans Tech Publications, Ltd.
Cited by
1 articles.
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1. Research on Machine Learning Based Fault Diagnosis Methods for Power Transformers;2023 IEEE 5th International Conference on Civil Aviation Safety and Information Technology (ICCASIT);2023-10-11