ABSTRACT

Outdoor thermal comfort is the key for creating vibrant outdoor urban spaces. Current practice for designing outdoor thermal comfort is based on simple design guidelines, and knowledge of local wind and sun patterns. In this paper we developed a predicting Outdoor Thermal Comfort model. This prediction of thermal comfort based on air temperature, global temperature, air velocity and humidity using Artificial Neural Network in Baharia Oasis. Results show that Thermal comfort level in Baharia Oasis is better in April, and October. This research confirmed a tool that can be developed for predicting comfort across a proposed development in Baharia Oasis location; we test the proposed design changes for their success during the design phase. Keywords: Thermal Comfort; Neural Network; Humidity; Temprature ; Velocity
Publication date: 01/11/2020

https://ijbpas.com/pdf/2020/November/MS_IJBPAS_2020_5255.pdf

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https://doi.org/10.31032/IJBPAS/2020/9.11.5255