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Analysis and prediction of thermal comfort using artificial neural network in baharia and kufra oases / Amal Ali Mousa Abdelkader ; Supervised Fawzia Ibrahim Moursy , Reda Abdelwahab , Gamil Gamal Abdelmotey

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Amal Ali Mousa Abdelkader , 2019Description: 119 P. : charts , facsimiles ; 25cmOther title:
  • تحليل الراحة الحرارية والتنبؤ بها باستخدام الشبكات العصبية الاصطناعية فى كل من الواحات البحرية والكفرة [Added title page title]
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Dissertation note: Thesis (M.Sc) - Cairo University - Faculty of African Postgraduate Studies - Department of Natural Resources Summary: 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
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.16.03.M.Sc.2019.Am.A (Browse shelf(Opens below)) Not for loan 01010110080628000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.16.03.M.Sc.2019.Am.A (Browse shelf(Opens below)) 80628.CD Not for loan 01020110080628000

Thesis (M.Sc) - Cairo University - Faculty of African Postgraduate Studies - Department of Natural Resources

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

Issued also as CD

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