A Genetic Programming Based Fuzzy Model for Fault Diagnosis of Power Transformers

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@InProceedings{Zhang:2010:ICINIS,
  author =       "Zheng Zhang and Kangling Fang and Weihua Huang",
  title =        "A Genetic Programming Based Fuzzy Model for Fault
                 Diagnosis of Power Transformers",
  booktitle =    "3rd International Conference on Intelligent Networks
                 and Intelligent Systems (ICINIS 2010)",
  year =         "2010",
  month =        "1-3 " # nov,
  pages =        "455--458",
  abstract =     "In this paper, a fuzzy model based on genetic
                 programming (GPFM) is proposed to diagnose the fault
                 types of insulation of power transformers. The proposed
                 GPFM algorithm constructs the fuzzy relationship
                 between input and output fuzzy variables by genetic
                 programming algorithms. The parameters of memberships
                 of fuzzy subsets and the fuzzy relationship of system
                 are represented by the GP candidates that have the form
                 of tree-like combinations of fuzzy subsets of input
                 variables. Then the best fuzzy function is evolved by
                 genetic operations and evolution. Based on the proposed
                 GPFM algorithms, an insulation fault diagnosis system
                 for power systems is designed to distinguish the
                 insulation fault types of power transformers. Compared
                 with the conditional fuzzy IEC code method, the GPFM
                 algorithm can automatically generate fuzzy relationship
                 between fault symptom with fault types and shows better
                 performances.",
  keywords =     "genetic algorithms, genetic programming, fuzzy IEC
                 code method, fuzzy subsets, genetic programming based
                 fuzzy model, insulation fault diagnosis system, power
                 transformers, tree-like combinations, fuzzy set theory,
                 power transformers",
  DOI =          "doi:10.1109/ICINIS.2010.154",
  notes =        "Coll. of Inf. Sci. & Eng., Wuhan Univ. of Sci. &
                 Technol., Wuhan, China. Also known as \cite{5693583}",
}

Genetic Programming entries for Zheng Zhang Kangling Fang Weihua Huang

Citations