A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers-Reference-Cited by-同舟云学术

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A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

Published:2017-03-01 Issue:2 Volume:12 Page:830-839
ISSN:1975-0102
Container-title:Journal of Electrical Engineering and Technology
language:en
Short-container-title:Journal of Electrical Engineering and Technology

Author:

Zhang Yiyi,Wei Hua,Liao Ruijin,Wang Youyuan,Yang Lijun,Yan Chunyu

Publisher

The Korean Institute of Electrical Engineers

Subject

Electrical and Electronic Engineering

Link

http://ocean.kisti.re.kr/downfile/crosscheck/kiee/JAKO201709641401802.pdf

Cited by 33 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. A comprehensive evaluation method for moisture and aging state of oil-immersed paper bushings based on dielectric modulus and K-nearest neighbor algorithm;Frontiers in Energy Research;2024-01-12

3. Hybrid DGA Method for Power Transformer Faults Diagnosis Based on Evolutionary k-Means Clustering and Dissolved Gas Subsets Analysis;IEEE Transactions on Dielectrics and Electrical Insulation;2023-10

4. Improvement of power transformer fault diagnosis by using sequential Kalman filter sensor fusion;International Journal of Electrical Power & Energy Systems;2023-07

5. Research on an Abnormal Recognition Method of the UHV Reactor Based on the DAGMM;Journal of Physics: Conference Series;2023-06-01

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