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Modified Harmony Search Algorithm and Neural Networks for Concrete Mix Proportion Design

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dc.contributor.authorLee, Joo-Ha-
dc.contributor.authorYoon, Young-Soo-
dc.date.accessioned2021-09-08T21:09:23Z-
dc.date.available2021-09-08T21:09:23Z-
dc.date.issued2009-01-
dc.identifier.issn0887-3801-
dc.identifier.issn1943-5487-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/120842-
dc.description.abstractThis study proposes a new methodology with harmony search (HS) algorithm and neural networks (NNs) for concrete mix proportioning. The basic procedure for the methodology consists of four steps: (1) constructing a database of mix designs; (2) establishing appropriate models for strength and workability; (3) optimizing mix proportion using the modified HS algorithm; and (4) refining the mixture using NNs. The proposed methodology could be a useful decision-making tool for concrete mix design.-
dc.format.extent5-
dc.language영어-
dc.language.isoENG-
dc.publisherASCE-AMER SOC CIVIL ENGINEERS-
dc.titleModified Harmony Search Algorithm and Neural Networks for Concrete Mix Proportion Design-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1061/(ASCE)0887-3801(2009)23:1(57)-
dc.identifier.scopusid2-s2.0-58149230898-
dc.identifier.wosid000263969700008-
dc.identifier.bibliographicCitationJOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.23, no.1, pp 57 - 61-
dc.citation.titleJOURNAL OF COMPUTING IN CIVIL ENGINEERING-
dc.citation.volume23-
dc.citation.number1-
dc.citation.startPage57-
dc.citation.endPage61-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryEngineering, Civil-
dc.subject.keywordPlusHIGH-PERFORMANCE CONCRETE-
dc.subject.keywordPlusCOMPRESSIVE STRENGTH-
dc.subject.keywordPlusPREDICTION-
dc.subject.keywordAuthorOptimization models-
dc.subject.keywordAuthorComputer aided design-
dc.subject.keywordAuthorHigh strength concrete-
dc.subject.keywordAuthorMaterial properties-
dc.subject.keywordAuthorCompressive strength-
dc.subject.keywordAuthorAlgorithms-
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