An Estimation Proposal for Engineering Properties of Modified Concrete by using Standalone and Hybrid GRELM

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dc.contributor.authorCemalgil, Selim
dc.contributor.authorOnat, Onur
dc.contributor.authorAruntas, Hueseyin Yilmaz
dc.date.accessioned2024-08-04T20:53:13Z
dc.date.available2024-08-04T20:53:13Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe presented study pertains to an attempt to propose a novel prediction model to predict the flexural and compressive strengths of concrete modulated using steel fiber (SFb) and silica fume (SF). A completed experimental investigation is adopted for the current study, and a research plan is employed. Three different superplasticizers amount (SP), different SF replacement ratios, and a constant amount of SFb were used by the weight of cement to meet the C25 target strength. A sum of 16 distinct mixtures designed by changing SP and SF ratios were developed. Furthermore, SFb was added at a fixed rate of 65 kg/m(3) to all planned concrete mixes. In addition, SFb was used to create a 16-mix design. Finally, a total of 32 distinct mix designs were created. Produced, hardened specimens were exposed to two different curing conditions. This research uses the mechanical characteristics of concrete treated with SF, SP, and SFb to estimate by conducting standalone and hybridized generalized extreme learning machine (GRELM) algorithms based on available experimental data in terms of the metaheuristic aspects of this work. With continuous input data, four separate data sets were constructed. Compressive strength and flexural strength were estimated separately. With the aid of the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms, binary and ternary hybrid approaches were developed and tested on the data. Four distinct estimation models were suggested. Two quality metrics were used to evaluate the estimation performance: Root Mean Square Error (RMSE) and correlation of determination (R-2). The estimation results showed that the hybridized GRELM-PSO-GWO estimation model that was built for prediction was relatively successful in all sets.en_US
dc.description.sponsorshipScientific Research Projects Committee of Gazi University, Ankara, Turkey [07/2002-39]en_US
dc.description.sponsorshipThe financial support for the experimental part of this study was provided by Scientific Research Projects Committee of Gazi University, Ankara, Turkey (Project no: 07/2002-39). Their support was gratefully acknowledged.en_US
dc.identifier.doi10.1007/s40996-022-01005-6
dc.identifier.endpage1377en_US
dc.identifier.issn2228-6160
dc.identifier.issn2364-1843
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85143292318en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1357en_US
dc.identifier.urihttps://doi.org/10.1007/s40996-022-01005-6
dc.identifier.urihttps://hdl.handle.net/11616/101034
dc.identifier.volume47en_US
dc.identifier.wosWOS:000912868900001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Int Publ Agen_US
dc.relation.ispartofIranian Journal of Science and Technology-Transactions of Civil Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectModified concreteen_US
dc.subjectGrey wolf optimizationen_US
dc.subjectCompressive strengthen_US
dc.subjectGRELMen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectFlexural strengthen_US
dc.titleAn Estimation Proposal for Engineering Properties of Modified Concrete by using Standalone and Hybrid GRELMen_US
dc.typeArticleen_US

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