Estimation of solar radiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey
| dc.contributor.author | Koca, Ahmet | |
| dc.contributor.author | Öztop, Hakan Fehmi | |
| dc.contributor.author | Varol, Yasin | |
| dc.contributor.author | Koca, Gonca Ozmen | |
| dc.date.accessioned | 2026-08-12T17:46:13Z | |
| dc.date.issued | 2011 | |
| dc.department | Fırat Üniversitesi | |
| dc.description.abstract | An artificial neural network (ANN) model was used to estimate the solar radiation parameters for seven cities from Mediterranean region of Anatolia in Turkey. As well known that Turkey is a bridge between Asia and Europe and it lies in a sunny belt, between 36 degrees and 42 degrees N latitudes. Indeed, the country has sufficient solar radiation intensities for solar applications. In order to make estimation of solar radiation, the data from the Turkish State and Meteorological Service were used. Data of 2006 were used for testing and data of 2005, 2007, and 2008 were estimated. Effects of number of input parameters were tested on solar radiation that was output layer. With this aim, number of input layer parameters changed from 2 to 6. The obtained results indicated that the method could be used by researchers or scientists to design high efficiency solar devices. It was also found that number of input parameters was the most effective parameter on estimation of future data on solar radiation. (C) 2011 Elsevier Ltd. All rights reserved. | |
| dc.identifier.doi | 10.1016/j.eswa.2011.01.085 | |
| dc.identifier.endpage | 8762 | |
| dc.identifier.issn | 0957-4174 | |
| dc.identifier.issn | 1873-6793 | |
| dc.identifier.issue | 7 | |
| dc.identifier.orcid | 0000-0003-2989-7125 | |
| dc.identifier.orcid | 0000-0003-1750-8479 | |
| dc.identifier.orcid | 0000-0002-0137-6988 | |
| dc.identifier.scopus | 2-s2.0-79952450583 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.startpage | 8756 | |
| dc.identifier.uri | https://doi.org/10.1016/j.eswa.2011.01.085 | |
| dc.identifier.uri | https://hdl.handle.net/11508/60997 | |
| dc.identifier.volume | 38 | |
| dc.identifier.wos | WOS:000289047700095 | |
| dc.identifier.wosquality | Q1 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Pergamon-Elsevier Science Ltd | |
| dc.relation.ispartof | Expert Systems with Applications | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_WoS_20260511 | |
| dc.subject | Solar radiation | |
| dc.subject | Mediterranean region of Anatolia | |
| dc.subject | Artificial neural network | |
| dc.title | Estimation of solar radiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey | |
| dc.type | Article |







