Prediction of dissolved gas Content in transformer oil based on Genetic Programming and DGA

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@InProceedings{WeiChang:2011:TMEE,

• author = "Wei Chang and Ning Hao",
• title = "Prediction of dissolved gas Content in transformer oil based on Genetic Programming and DGA",
• booktitle = "International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE 2011)",
• year = "2011",
• month = "16-18 " # dec,
• pages = "1133--1136",
• address = "Changchun, China",
• size = "4 pages",
• 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.",
• 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",
• DOI = "doi:10.1109/TMEE.2011.6199404",
• notes = "Also known as \cite{6199404}",

}

Genetic Programming entries for Wei Chang Ning Hao

Citations