Comparison of modelling ANN and ELM to estimate solar radiation over Turkey using NOAA satellite data

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dc.authoridsahin, mehmet/0000-0001-7942-9253
dc.contributor.authorSahin, Mehmet
dc.date.accessioned2024-12-24T19:28:02Z
dc.date.available2024-12-24T19:28:02Z
dc.date.issued2013
dc.departmentSiirt Üniversitesi
dc.description.abstractIn this study, solar radiation (SR) is estimated at 61 locations with varying climatic conditions using the artificial neural network (ANN) and extreme learning machine (ELM). While the ANN and ELM methods are trained with data for the years 2002 and 2003, the accuracy of these methods was tested with data for 2004. The values for month, altitude, latitude, longitude, and land-surface temperature (LST) obtained from the data of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite are chosen as input in developing the ANN and ELM models. SR is found to be the output in modelling of the methods. Results are then compared with meteorological values by statistical methods. Using ANN, the determination coefficient (R-2), mean bias error (MBE), root mean square error (RMSE), and Willmott's index (WI) values were calculated as 0.943, -0.148 MJm(-2), 1.604 MJm(-2), and 0.996, respectively. While R-2 was 0.961, MBE, RMSE, and WI were found to be in the order 0.045 MJm(-2), 0.672 MJm(-2), and 0.997 by ELM. As can be understood from the statistics, ELM is clearly more successful than ANN in SR estimation.
dc.identifier.doi10.1080/01431161.2013.822597
dc.identifier.endpage7533
dc.identifier.issn0143-1161
dc.identifier.issn1366-5901
dc.identifier.issue21
dc.identifier.scopus2-s2.0-84884493877
dc.identifier.scopusqualityQ1
dc.identifier.startpage7508
dc.identifier.urihttps://doi.org/10.1080/01431161.2013.822597
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6900
dc.identifier.volume34
dc.identifier.wosWOS:000324459800006
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofInternational Journal of Remote Sensing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.titleComparison of modelling ANN and ELM to estimate solar radiation over Turkey using NOAA satellite data
dc.typeArticle

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