The Impact of Building Façade Reflectivity on Pedestrian Visual Comfort with the Application of Bayesian Structural Equation Modeling
Keywords:glare, structural equation modeling, Bayesian predictor, maximum likelihood predictor, building façade reflectivity
The rapid urban development promotes the need for skyscrapers, which vastly adopt a modern architecture design using reflective materials on the façade of the building, particularly for the aesthetic purpose. Nevertheless, outdoor glare or reflected daylight from a highly reflective building façade may cause visual and thermal discomforts for the residents in the neighborhood buildings and outdoor pedestrians. This might cause uncomfortable glare for individuals outside the building. The amount of glare will be higher as a result of greater solar radiation obtained all year round in tropical countries. Regression and presently structural equation modeling are the best-known statistical modeling in approximating the connection between building facade reflectivity and pedestrian’s visual performance. Nevertheless, those methodologies have their own limitations. The primary aim of this research is to compare the effect of building facade reflectivity on pedestrian visual comfort by using four core statistical approximation approaches which include regression, partial least square, structural equation modeling with maximum likelihood estimator, and structural equation modeling with Bayesian estimator. The present study introduces a novel as well as practical modeling and predicting concepts for investigators and specialists in the building façade reflectivity study field.
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