Genetic Programming based Fuzzy Mapping Function Model for fault diagnosis of power transformers
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- @InProceedings{Zhang:2008:WCICA,
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author = "Zheng Zhang and Kangling Fang and Weihua Huang",
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title = "Genetic Programming based Fuzzy Mapping Function Model
for fault diagnosis of power transformers",
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booktitle = "7th World Congress on Intelligent Control and
Automation, WCICA 2008",
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year = "2008",
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month = "25-27 " # jun,
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address = "Chongqing, China",
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pages = "1184--1187",
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keywords = "genetic algorithms, genetic programming, fault
diagnosis, fuzzy IEC code method, genetic operations,
genetic programming based fuzzy mapping functions,
insulation fault diagnosis system, power systems, power
transformers, tree-like combinations, fault diagnosis,
fuzzy set theory, power transformer insulation",
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DOI = "doi:10.1109/WCICA.2008.4593092",
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abstract = "A genetic programming based fuzzy mapping functions
(GPFMF) model is proposed in this paper to diagnose the
insulation fault types of power transformers. The
proposed GPFMF model constructs the fuzzy relationship
between input and output fuzzy variables by genetic
programming algorithms. The fuzzy relationship is
represented as one of candidates which have the form of
tree-like combinations of series of fuzzy implication
operators with fuzzy input variables. Then the best
fuzzy mapping function is evolved by genetic operations
and evolution. Based on the proposed GPFMF model, an
insulation fault diagnosis system for power systems is
designed to detect the insulation fault types of power
transformers. Compared with the normal fuzzy IEC code
method, the GPFMF models can generate fuzzy mapping
functions from fuzzy input and output examples and has
higher performance than normal fuzzy method.",
-
notes = "Also known as \cite{4593092}",
- }
Genetic Programming entries for
Zheng Zhang
Kangling Fang
Weihua Huang
Citations