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https://hdl.handle.net/11499/8560
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Şencan Şahin, A. | - |
dc.contributor.author | Yazıcı, Hilmi | - |
dc.date.accessioned | 2019-08-16T12:42:29Z | |
dc.date.available | 2019-08-16T12:42:29Z | |
dc.date.issued | 2012 | - |
dc.identifier.issn | 0377-0273 | - |
dc.identifier.uri | https://hdl.handle.net/11499/8560 | - |
dc.identifier.uri | https://doi.org/10.1016/j.jvolgeores.2012.04.020 | - |
dc.description.abstract | In this study, energy and exergy analysis of the Afyon geothermal district heating system (AGDHS) in Afyon, Turkey using artificial neural network (ANN) and adaptive neuro-fuzzy (ANFIS) methods is carried out. Actual system data in the analysis of the AGDHS are used. The results of ANN are compared with ANFIS in which the same data sets are used. ANN model is slightly better than ANFIS in determining the energy and exergy rates. In addition, new formulations obtained from ANN are presented for the determination of the energy and exergy rates of the AGDHS. The R 2 -values obtained when unknown data were used in the networks were 0.999999847 and 0.99999997 for the energy and exergy rates respectively, which are very satisfactory. © 2012 Elsevier B.V. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Journal of Volcanology and Geothermal Research | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Artificial neural network | en_US |
dc.subject | District heating | en_US |
dc.subject | Geothermal energy | en_US |
dc.subject | Neuro-fuzzy | en_US |
dc.subject | Thermodynamic analysis | en_US |
dc.subject | Actual system | en_US |
dc.subject | Data sets | en_US |
dc.subject | Energy and exergy | en_US |
dc.subject | Energy and exergy analysis | en_US |
dc.subject | Geothermal district heating system | en_US |
dc.subject | Neuro-Fuzzy | en_US |
dc.subject | Thermo dynamic analysis | en_US |
dc.subject | Thermodynamic evaluation | en_US |
dc.subject | Exergy | en_US |
dc.subject | Geothermal heating | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Thermoanalysis | en_US |
dc.subject | artificial neural network | en_US |
dc.subject | exergy | en_US |
dc.subject | geothermal system | en_US |
dc.subject | heating | en_US |
dc.subject | thermodynamics | en_US |
dc.subject | Afyon | en_US |
dc.subject | Turkey | en_US |
dc.title | Thermodynamic evaluation of the Afyon geothermal district heating system by using neural network and neuro-fuzzy | en_US |
dc.type | Article | en_US |
dc.identifier.volume | 233-234 | en_US |
dc.identifier.startpage | 65 | |
dc.identifier.startpage | 65 | en_US |
dc.identifier.endpage | 71 | en_US |
dc.identifier.doi | 10.1016/j.jvolgeores.2012.04.020 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-84861013022 | en_US |
dc.identifier.wos | WOS:000306617100006 | en_US |
dc.identifier.scopusquality | Q1 | - |
dc.owner | Pamukkale University | - |
item.openairetype | Article | - |
item.grantfulltext | none | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection Teknik Eğitim Fakültesi Koleksiyonu WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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