Prediction of dissolved gas Content in transformer oil based on Genetic Programming and DGA
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{WeiChang:2011:TMEE,
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author = "Wei Chang and Ning Hao",
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title = "Prediction of dissolved gas Content in transformer oil
based on Genetic Programming and DGA",
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booktitle = "International Conference on Transportation,
Mechanical, and Electrical Engineering (TMEE 2011)",
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year = "2011",
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month = "16-18 " # dec,
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pages = "1133--1136",
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address = "Changchun, China",
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size = "4 pages",
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abstract = "Genetic Programming (GP), which is suitable for
prediction, is combined with transformer oil dissolved
gas analysis (DGA), and also a method of the prediction
of dissolved gas Content in transformer oil based on GP
classification algorithm is proposed, so as to
predicting the operational status and the latent faults
of a power transformer effectively. The comparative
results show that GP model can improve the prediction
accuracy effectively.",
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keywords = "genetic algorithms, genetic programming, DGA, GP
classification algorithm, dissolved gas content
prediction, power transformer, transformer oil
dissolved gas analysis, chemical analysis, power
transformer insulation, transformer oil",
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DOI = "doi:10.1109/TMEE.2011.6199404",
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notes = "Also known as \cite{6199404}",
- }
Genetic Programming entries for
Wei Chang
Ning Hao
Citations