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Analysis Using ANN of Thermal Inertia in the Sahara Habitats: The Case of Architectural Styles in the Region of Adrar (Algeria)
Current Issue
Volume 1, 2014
Issue 4 (September)
Pages: 69-72   |   Vol. 1, No. 4, September 2014   |   Follow on         
Paper in PDF Downloads: 13   Since Aug. 28, 2015 Views: 1586   Since Aug. 28, 2015
Authors
[1]
Bouharati Saddek, Laboratory of Intelligent Systems, Faculty of Technology, UFAS Setif1 University, Algeria; Faculty of Natural Sciences and Life, UFAS Setif1 University, Algeria.
[2]
Braham-Chaouch Wafa, Research Unit renewable Saharan Environments (URER. MS), Adrar, Algeria.
[3]
Benzidane Chahra, Faculty of Natural Sciences and Life, UFAS Setif1 University, Algeria.
[4]
Boumaïza Souad, Faculty of Natural Sciences and Life, UFAS Setif1 University, Algeria.
Abstract
Architecture Saharan thermal inertia is a key element of environmental management. Whatever the desired inertia, materials need to be adapted for this purpose. It depends on the chosen comfort; absorption of inertia makes use of dense materials with high thermal capacity (land, brick tablet). The inertia of the transmission, in turn, requires a material with absorption and rapid return of heat. The nature of the material used to absorb or diffuse the heat, thickness walls; architectural geometries have a very complex role. In this study, we propose a model for analyzing these variables through the techniques of artificial intelligence such as artificial neural networks.
Keywords
Air Pollution, Air Quality, Artificial Intelligence, Fuzzy Logic
Reference
[1]
Guerrout. Ch. (2007). L’ancien hôpital de la ville d’Adrar, Revue En-Nakhla, n°3, p.22-26.
[2]
Godard. C. (1954). L’oasis moderne, Essai d’urbanisme saharien, La maison des livres, Alger.
[3]
Lequellec J-L.. (2006). Maisons du Sahara : Habiter le désert, éditions Hazan.
[4]
Bouharati S., Benamrani H., Alleg F., Benzidane C., Bounechada M. (2013). Artificial Neural Networks In Prevention Of Nosocomials Infections. International journal of scientific & technology research volume 2, issue 10, october 2013.
[5]
C. William, MD. Hanson III, Bryan E., Marshall, MD, FRCP, FRCA. (2000). “Artificial intelligence applications in the intensive care unit”. Crit Care Med Vol. 29, No. 2.
[6]
Ajith A. (2001). “Neuro Fuzzy Systems: state of Art Modelling Techniques”, In proceedings of the sixth international work conference on Artificial and Natural Neural Networks, IWANN, Granada, Springer Verlag Germany, pp.269-276.
[7]
Ajith A. (2005).“Adaptation of Fuzzy Inference System Using Neural Learning”, Computer Science Department, Oklahoma State University, USA, springer verlag berlin Heidelberg.
[8]
Nikam S.R., Nikumbh P.J., Kulkarni S.P. (2012).“Fuzzy Logic And Neuro-Fuzzy Modeling”. MPGI National Multi Conference (MPGINMC2012) 7-8.
[9]
Chen D.G., Haregreaves N.B., Ware D.M., and Liu Y. (2000). “A Fuzzy logic model with genetic algorithm for analyzing fish stock-recruitment relationships”. Can J. Fish. Aquat. Sci., 57:1878-1887.
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