Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/723
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dc.contributor.authorİnce, İsmail-
dc.contributor.authorBozdağ, Ali-
dc.contributor.authorFener, Mustafa-
dc.contributor.authorKahraman, Sair-
dc.date.accessioned2021-12-13T10:29:52Z-
dc.date.available2021-12-13T10:29:52Z-
dc.date.issued2019-
dc.identifier.issn1866-7511-
dc.identifier.issn1866-7538-
dc.identifier.urihttps://doi.org/10.1007/s12517-019-4953-4-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/723-
dc.description.abstractCompressive strength of rocks is an important factor in structural design in rock engineering. Compressive strength can be determined in the laboratory by means of the uniaxial compressive strength (UCS) test, or it can be estimated indirectly by simple experiments such as point load strength (PLT) test and Schmidt hammer rebound test. Although the UCS test method is time-consuming and expensive, it is simple when compared to other methods. Therefore, many studies have been performed to estimate UCS values of rocks. Studies indicated that correlation coefficient of rock groups is low unless they are classified as metamorphic, sedimentary, or volcanic. Pyroclastic rocks are widely used as construction materials because of the fact that they crop out over extensive areas in the world. To estimate the UCS values of pyroclastic rocks in Central and Western Anatolia region, Turkey, multiple linear regression (MLR) analysis and gene expression programming (GEP) were employed and during the analysis, and PLT, rho(d), rho(s), and n were used as the independent variables. Based on the analysis results, it was detected that the GEP methods gave better results than MLR method. Additionally, the correlation coefficient (R-2) values of training and sets of validation of the GEP-I model are 0.8859 and 0.9325, respectively, and this model, thereby, is detected the best of generation individuals for prediction of the UCS.en_US
dc.language.isoenen_US
dc.publisherSPRINGER HEIDELBERGen_US
dc.relation.ispartofARABIAN JOURNAL OF GEOSCIENCESen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectUniaxial Compressive Strength (Ucs)en_US
dc.subjectPyroclastic Rocksen_US
dc.subjectGene Expression Programming (Gep)en_US
dc.subjectMultiple Linear Regression (Mlr)en_US
dc.subjectConstruction Materialsen_US
dc.subjectPoint-Load Strengthen_US
dc.subjectOpen-Pit Mineen_US
dc.subjectTensile-Strengthen_US
dc.subjectNeural-Networksen_US
dc.subjectPredictionen_US
dc.subjectFuzzyen_US
dc.subjectFlowen_US
dc.subjectDeteriorationen_US
dc.subjectParametersen_US
dc.subjectCriterionen_US
dc.titleEstimation of uniaxial compressive strength of pyroclastic rocks (Cappadocia, Turkey) by gene expression programmingen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s12517-019-4953-4-
dc.identifier.scopus2-s2.0-85076129152en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Jeoloji Mühendisliği Bölümüen_US
dc.authorwosidince, ismail/AAA-3236-2021-
dc.identifier.volume12en_US
dc.identifier.issue24en_US
dc.identifier.wosWOS:000506412300011en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid16555121900-
dc.authorscopusid57211604468-
dc.authorscopusid14522411400-
dc.authorscopusid7005541488-
dc.identifier.scopusqualityQ2-
item.cerifentitytypePublications-
item.grantfulltextembargo_20300101-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.fulltextWith Fulltext-
crisitem.author.dept02.07. Department of Geological Engineering-
crisitem.author.dept02.07. Department of Geological Engineering-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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