Case-based reasoning approach to estimating the strength of sustainable concrete

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dc.contributor.authorKoo, Choongwanko
dc.contributor.authorJin, Ruoyuko
dc.contributor.authorLi, Boko
dc.contributor.authorCha, Seung Hyunko
dc.contributor.authorWanatowski, Dariuszko
dc.date.accessioned2021-09-03T05:11:14Z-
dc.date.available2021-09-03T05:11:14Z-
dc.date.created2021-09-03-
dc.date.created2021-09-03-
dc.date.issued2017-12-
dc.identifier.citationCOMPUTERS AND CONCRETE, v.20, no.6, pp.645 - 654-
dc.identifier.issn1598-8198-
dc.identifier.urihttp://hdl.handle.net/10203/287593-
dc.description.abstractContinuing from previous studies of sustainable concrete containing environmentally friendly materials and existing modeling approach to predicting concrete properties, this study developed an estimation methodology to predicting the strength of sustainable concrete using an advanced case-based reasoning approach. It was conducted in two steps: (i) establishment of a case database and (ii) development of an advanced case-based reasoning model. Through the experimental studies, a total of 144 observations for concrete compressive strength and tensile strength were established to develop the estimation model. As a result, the prediction accuracy of the A-CBR model (i.e., 95.214% for compressive strength and 92.448% for tensile strength) performed superior to other conventional methodologies (e.g., basic case-based reasoning and artificial neural network models). The developed methodology provides an alternative approach in predicting concrete properties and could be further extended to the future research area in durability of sustainable concrete.-
dc.languageEnglish-
dc.publisherTECHNO-PRESS-
dc.titleCase-based reasoning approach to estimating the strength of sustainable concrete-
dc.typeArticle-
dc.identifier.wosid000422719600003-
dc.identifier.scopusid2-s2.0-85040181638-
dc.type.rimsART-
dc.citation.volume20-
dc.citation.issue6-
dc.citation.beginningpage645-
dc.citation.endingpage654-
dc.citation.publicationnameCOMPUTERS AND CONCRETE-
dc.identifier.doi10.12989/cac.2017.20.6.645-
dc.contributor.localauthorCha, Seung Hyun-
dc.contributor.nonIdAuthorKoo, Choongwan-
dc.contributor.nonIdAuthorJin, Ruoyu-
dc.contributor.nonIdAuthorLi, Bo-
dc.contributor.nonIdAuthorWanatowski, Dariusz-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorsustainable concrete-
dc.subject.keywordAuthoradvanced case-based reasoning-
dc.subject.keywordAuthorenvironmentally friendly concrete materials-
dc.subject.keywordAuthorconcrete mixture design-
dc.subject.keywordAuthorconcrete strength prediction-
dc.subject.keywordAuthoroptimization process-
dc.subject.keywordPlusWASTE CARPET FIBERS-
dc.subject.keywordPlusCOMPRESSIVE STRENGTH-
dc.subject.keywordPlusGREEN CONCRETE-
dc.subject.keywordPlusENGINEERING PROPERTIES-
dc.subject.keywordPlusAGGREGATE CONCRETE-
dc.subject.keywordPlusRECYCLED CONCRETE-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusCO2 EMISSIONS-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusPREDICTION-
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