This study looks at the effect of daylighting on human performance. It includes a focus on glare index combined with the actual feeling of users of the classroom as a way to assess indoor lighting quality. The main objective of this research is to understand the impact of daylighting from windows on the glare sensation and also to determine which glare index is the closest to human visual sensation under local daylighting conditions in Biskra, Algeria with highly luminous climate. The study used High Dynamic Range (HDR) photography, Evaglare and Aftab Alpha software to calculate the two glare metrics Daylight Glare, Index (DGI) and the Daylight Glare Probability (DGP). A survey was also used with 90 occupants under different lighting conditions (different configurations) in a design classroom. In order to link the mathematical model and the human assessment of glare, statistical regression analysis was used. We established a statistically compelling connection between daylighting and student performance
The present work compares the ability of the two most used glare indices, the Daylight Glare Probability (DGP) and the International Commission on Illumination (CIE) Glare Index (CGI), using Multiple Correspondence Analysis (MCA) and Artificial Neural Networks (ANN). The research investigates the efficiency of indexes in predictive indoor lighting quality. This study was carried out by analyzing data from a survey administered to ninety students in real design classrooms in the city of Biskra, Algeria. The experiment was conducted using three different lighting indoor conditions: natural and artificial lighting and mixed lighting. The true prediction of the Daylight Glare Probability for the variable Comfortable was 60.60%, and for (CIE) Glare Index the prediction values were equal to 44.60% for the same variable
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