ESTIMATING SOLAR RADIATION BY MACHINE LEARNING METHODS

dc.contributor.author	Ertugrul, Edip
dc.contributor.author	Sahin, Mehmet
dc.contributor.author	Aggun, Fikri
dc.date.accessioned	2021-12-16T09:07:56Z
dc.date.available	2021-12-16T09:07:56Z
dc.date.issued	2015
dc.identifier.isbn	978-1-4673-7386-9
dc.identifier.issn	2165-0608
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10564
dc.description.abstract	Solar energy, which is clean and renewable energy source, is a popular subject. The estimation of solar radiation can be done instead of long term measurements. Therefore, the satellite and meteorological values of 53 different locations of Turkey were us
dc.language.iso	Turkish
dc.publisher	Ieee
dc.relation.ispartof	23nd Signal Processing and Communications Applications Conference (SIU)
dc.source	2015 23Rd Sıgnal Processıng And Communıcatıons Applıcatıons Conference (Sıu)
dc.title	ESTIMATING SOLAR RADIATION BY MACHINE LEARNING METHODS
dc.type	Proceedings Paper
dc.identifier.startpage	1611
dc.identifier.endpage	1614
dc.identifier.wos	WOS:000380500900383

Files in this item

Files	Size	Format	View
There are no files associated with this item.