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DC Field | Value | Language |
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dc.contributor.author | Özbayoğlu, Ahmet Murat | - |
dc.contributor.author | Özbayoğlu, Mehmet Evren | - |
dc.contributor.author | Özbayoğlu, Gülhan | - |
dc.date.accessioned | 2021-01-18T06:01:53Z | - |
dc.date.available | 2021-01-18T06:01:53Z | - |
dc.date.issued | 2012-09 | - |
dc.identifier.citation | Ozbayoglu, A.M., Ozbayoglu, M.E. and Ozbayoglu, G., “Comparison of Gross Calorific Value Estimation of Turkish Coals using Regression and Neural Networks Techniques”, XXVIth International Mineral Processing Congress (IMPC 2012), Paper No: 420, pp. 4011-4023, Yeni Delhi, Hindistan, 24-28 Eylül, 2012. | en_US |
dc.identifier.isbn | 8190171437 | - |
dc.identifier.isbn | 978-819017143-4 | - |
dc.identifier.uri | http://www.impc-council.com/IMPC_2012_Proceedings_INDIA.pdf | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/3966 | - |
dc.description | 26th International Mineral Processing Congress, IMPC (2012 : New Delhi; India) | en_US |
dc.description.abstract | Gross calorific value (GCV) of coals was estimated using artificial neural networks, linear and non- linear regression techniques. Proximate and ultimate analysis results were collected for 187 different coal samples. Different input data sets were compared, such as both proximate and ultimate analysis data, and only proximate analysis data and only ultimate analysis data. It was observed that the best results were obtained when both proximate analysis and ultimate analysis results were used for estimating the gross calorific value. When the performance of artificial neural networks and regression analysis techniques were compared, it was observed that both artificial neural networks and regression techniques were promisingly accurate in estimating gross calorific values. In general, most of the models estimated the gross calorific value within ±3% of the expected value. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Metso,Vale,Tata Steel,ESSAR STEEL,TATA CONSULTANCY SERVICE | en_US |
dc.relation.ispartof | XXVIth International Mineral Processing Congress (IMPC 2012) | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.subject | lignites | en_US |
dc.subject | gross calorific value | en_US |
dc.subject | proximate analysis | en_US |
dc.subject | ultimate analysis | en_US |
dc.subject | regression | en_US |
dc.subject | neural networks | en_US |
dc.title | Comparison of Gross Calorific Value Estimation of Turkish Coals Using Regression and Neural Networks Techniques | en_US |
dc.type | Conference Object | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | tr_TR |
dc.identifier.startpage | 4011 | en_US |
dc.identifier.endpage | 4023 | en_US |
dc.authorid | 0000-0001-7998-5735 | - |
dc.identifier.scopus | 2-s2.0-84879950552 | en_US |
dc.institutionauthor | Özbayoğlu, Ahmet Murat | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.1. Department of Artificial Intelligence Engineering | - |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
Files in This Item:
File | Description | Size | Format | |
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Ozbayoglu_420.pdf | 1.21 MB | Adobe PDF | View/Open |
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