الفهرس 
Analysis and prediction of thermal comfort using artificial neural network in baharia and kufra oases
AbstractOnly 14 pages are availabe for public view
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Abstract
Outdoor thermal comfort is the key to creating vibrant outdoor urban spaces.The built form can modify solar radiation and wind. However, there is currently no way of considering the effect of the built form on thermal comfort when designing a new development based on the environmental factors{u2013} wind, solar radiation, and ambient temperature. Current practice for designing outdoor thermal comfort is based on simple design guidelines, and knowledge of local wind and sun patterns. A Process for Predicting Outdoor thermal comfort has been developed.This predicts thermal comfort based on air temperature, global temperature, air velocity and humidity using Artificial Neural Network in Baharia Oasis and Al Kufra locations.The proposed Artificial Neural Network based on the following six major components, weighting factors, summation function (NET), the transfer function (TF), the output function, the error function and back-propagated value and the learning function