Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7650
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dc.contributor.authorLiang, Yongen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-29T05:04:12Z-
dc.date.available2023-03-29T05:04:12Z-
dc.date.issued2002-
dc.identifier.citationProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, 2002, Vol. 1, pp. 789 - 794, Article number 1007026en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7650-
dc.description.abstractIn this paper, a new two-way adaptive search mutation strategy is proposed, and a "two-way evolution strategy" (TWES) is established. The experimental results show that TWES yields much faster convergence than classical evolution strategies. This paper also discusses the relationship between the parameter setting and the convergent speed by TWES. © 2002 IEEE.en_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002en_US
dc.titleTwo-way mutation evolution strategiesen_US
dc.typeConference Proceedingsen_US
dc.identifier.doi10.1109/CEC.2002.1007026-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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