The Luminance Estimation of Basketball Halls Using Machine Learning Methods
Yükleniyor...
Dosyalar
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Indoor sports halls are places in which artificial lighting is needed and lighting should be monitored in order toprovide a healthy sports environment. It is of utmost importance for maintaining player performances and theirhealth and the visual ability and comfort of the spectator watching matches on TV. Lighting should bemaintained and monitored in a planned manner starting from the construction period. It takes a long of period oftime to perform measurements using point measuring tools in indoor sports halls. In this study, the luminanceestimation of an indoor sports hall was made using machine learning techniques in order to find a solution to thisproblem. In order to form the data set, 91 reference points were identified according to the standards in the sportshall. The luminance of these points was measured and pixel values of these points (R, G, B) were identified onthe photograph taken. 91 reference points were randomly categorized as training data (70%) and test data (30%).In the study, Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) techniques were used asmachine learning methods. The mean square error (MSE), the root mean square error (RMSE), the correlationcoefficient and the accuracy rate methods were used in order to test the success rate of these techniques.
Açıklama
Anahtar Kelimeler
Kaynak
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
8
Sayı
4
