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A genetic algorithms for on-line calculation with application to system theory

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dc.contributor.authorLee, H. G.-
dc.contributor.authorHong, J. M.-
dc.contributor.authorKang, H.-
dc.contributor.authorSim, K. B.-
dc.date.accessioned2021-12-29T00:41:08Z-
dc.date.available2021-12-29T00:41:08Z-
dc.date.issued2009-
dc.identifier.issn1098-7584-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/52757-
dc.description.abstractEven though the genetic algorithm is known to be a very effective method to solve the global minimization problem, it needs much time (a large population size and a large number of generations) for a reliable answer and thus it seems to be inadequate for on-line performance. We propose a population feedback GA scheme. we show the effectiveness Of our scheme by finding an observer for the discrete-time nonlinear autonomous systems with simulations.-
dc.format.extent3-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE-
dc.titleA genetic algorithms for on-line calculation with application to system theory-
dc.typeArticle-
dc.identifier.doi10.1109/FUZZY.2009.5277057-
dc.identifier.bibliographicCitation2009 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3, pp 2180 - 2182-
dc.description.isOpenAccessN-
dc.identifier.wosid000274242600382-
dc.identifier.scopusid2-s2.0-71249114389-
dc.citation.endPage2182-
dc.citation.startPage2180-
dc.citation.title2009 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3-
dc.type.docTypeProceedings Paper-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryMathematics, Applied-
dc.description.journalRegisteredClassscopus-
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