Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6661
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dc.contributor.authorÖzbayoğlu, Gülhan-
dc.contributor.authorÖzbayoğlu, Ahmet Murat-
dc.contributor.authorÖzbayoğlu, M. Evren-
dc.date.accessioned2021-09-11T15:43:06Z-
dc.date.available2021-09-11T15:43:06Z-
dc.date.issued2008en_US
dc.identifier.issn0301-7516-
dc.identifier.issn1879-3525-
dc.identifier.urihttps://doi.org/10.1016/j.minpro.2007.08.003-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6661-
dc.description.abstractIn this research, different techniques for the estimation of coal HGI values are studied. Data from 163 sub-bituminous coals from Turkey are used by featuring I I coal parameters, which include proximate analysis, group maceral analysis and rank. Nonlinear regression and neural network techniques are used for predicting the HGI values for the specified coal parameters. Results indicate that a hybrid network which is a combination of 4 separate neural networks gave the most accurate HGI prediction and all of the neural network models, outperformed non-linear regression in the estimation process. (C) 2007 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofInternational Journal of Mineral Processingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHardgrove grindability indexen_US
dc.subjectTurkish coalsen_US
dc.subjectneural networksen_US
dc.subjectnon-linear regressionen_US
dc.subjectproximate analysisen_US
dc.subjectpetrographic analysisen_US
dc.titleEstimation of Hardgrove grindability index of Turkish coals by neural networksen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume85en_US
dc.identifier.issue4en_US
dc.identifier.startpage93en_US
dc.identifier.endpage100en_US
dc.authorid0000-0001-7998-5735-
dc.identifier.wosWOS:000253168100003en_US
dc.identifier.scopus2-s2.0-37549050498en_US
dc.institutionauthorÖzbayoğlu, Ahmet Murat-
dc.identifier.doi10.1016/j.minpro.2007.08.003-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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