Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11692
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dc.contributor.authorJovic Z.-
dc.contributor.authorAnicic O.-
dc.contributor.authorMarsenic M.-
dc.contributor.authorNedic, Bogdan-
dc.date.accessioned2021-04-20T18:59:46Z-
dc.date.available2021-04-20T18:59:46Z-
dc.date.issued2016-
dc.identifier.issn0378-7788-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/11692-
dc.description.abstract© 2016 Elsevier B.V. Solar energy is very important alternative energy due to the vase deposit. The main goal of the study was to analyze the solar radiation based on the four parameters: mean sea level (MSL), dry-bulb temperature (DBT), wet-bulb temperature (WBT) and relative humidity (RH). Adaptive neuro-fuzzy inference system (ANFIS) was used in order to estimate the parameters influence on the solar radiation prediction. Variable selection process was used to select the most dominant factors which affect the solar radiation prediction. The results shown that the DBT and RH are the most dominant factors for the solar radiation prediction.-
dc.rightsrestrictedAccess-
dc.sourceEnergy and Buildings-
dc.titleSolar radiation analyzing by neuro-fuzzy approach-
dc.typearticle-
dc.identifier.doi10.1016/j.enbuild.2016.08.020-
dc.identifier.scopus2-s2.0-84982793307-
Appears in Collections:Faculty of Engineering, Kragujevac

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