Approximate and three-dimensional modeling of brightness levels in interior spaces by using artificial neural networks

ArticleAçık Erişim

Özet

In this study, artificial neural networks were used to determine the intensity of brightness in interior spaces. The illumination elements to illuminate indoor spaces were considered, not individually, but as a system. So, during the planned maintenance periods of an illumination system, after its design and installation, simple brightness level measurements must be taken. For a threedimensional evaluation of the brightness level in indoor spaces in a speedy and accurate manner, the obtained brightness level measurement results and artificial neural network model were used. Upon estimation of the most suitable brightness level for indoor spaces by using the artificial neutral network model, the energy demands required by the illumination elements decreased. Consequently, in this study, with estimations of brightness levels, the extent to which the artificial neutral networks become successful was observed and more correct results have been obtained in terms of both economy and usage. © 2015 The Korean Institute of Electrical Engineers.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/15167Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.5370/jeet.2015.10.4.1823Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorŞahin, Mustafa
dc.contributor.authorOğuz, Yüksel
dc.contributor.authorBüyüktümtürk, Fuat
dc.date.accessioned2026-10-18T20:29:57.481737343Z
dc.date.available2026-10-18T20:29:57.481737343Z
dc.date.issued2015
dc.description.abstractIn this study, artificial neural networks were used to determine the intensity of brightness in interior spaces. The illumination elements to illuminate indoor spaces were considered, not individually, but as a system. So, during the planned maintenance periods of an illumination system, after its design and installation, simple brightness level measurements must be taken. For a threedimensional evaluation of the brightness level in indoor spaces in a speedy and accurate manner, the obtained brightness level measurement results and artificial neural network model were used. Upon estimation of the most suitable brightness level for indoor spaces by using the artificial neutral network model, the energy demands required by the illumination elements decreased. Consequently, in this study, with estimations of brightness levels, the extent to which the artificial neutral networks become successful was observed and more correct results have been obtained in terms of both economy and usage. © 2015 The Korean Institute of Electrical Engineers.
dc.identifier.doi10.5370/jeet.2015.10.4.1823
dc.identifier.endpage1830
dc.identifier.issn1975-0102
dc.identifier.issue4
dc.identifier.scopus2-s2.0-84931087818
dc.identifier.startpage1823
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/15167
dc.identifier.volume10
dc.language.isoen
dc.publisherKorean Institute of Electrical Engineers
dc.relation.ispartofJournal of Electrical Engineering and Technology
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial neural networks
dc.subjectEstimation of brightness level
dc.subjectIllumination systems
dc.subjectThreedimensional modeling
dc.subjectLevel measurement
dc.subjectLuminance
dc.subjectArtificial neural network modeling
dc.subjectArtificial neutral network
dc.subjectEnergy demands
dc.subjectIllumination system
dc.subjectIndoor space
dc.subjectInterior space
dc.subjectPlanned maintenance
dc.subjectThree-dimensional model
dc.subjectNeural networks
dc.titleApproximate and three-dimensional modeling of brightness levels in interior spaces by using artificial neural networks
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus3
rdl.source.indexSCOPUS