Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.650890
Title: A hierarchically organised genetic algorithm for fuzzy network synthesis
Author: Filloy-García, Enrique Rafael
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2002
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Abstract:
A hierarchical, two-level genetic algorithm to produce the rules for a fuzzy system is proposed. The underlying architecture of fuzzy networks corresponds with the structured, two-level representations used. At one level, a variable-length structure was designed to represent entire rule sets as individuals in a population; at a lower level, another population contains elements which represent single fuzzy rules. The two populations co-evolve simultaneously in an interdependent fashion. This method has been shown to be capable of producing effective fuzzy systems of an adequate size for particular classes of problems; examples of a control task and a classification problem are shown. Suitable replacement strategies for the elements population were devised, introducing the definition of a heredity factor. Additionally, means for the adaptation of system parameters like cut & splice probabilities were developed to further enhance system performance.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.650890  DOI: Not available
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