DESIGN OPTIMIZATION OF REINFORCED CONCRETE BEAMS USING ARTIFICIAL NEURAL NETWORK

dc.contributor.author	Fathelrahman M Adam, فتح الرحمن محمد ادم
dc.contributor.author	Abdelrahman E. Mohamed, عبد الرحمن محمد
dc.contributor.author	Sara A. Babiker, سارة أ. بابكر
dc.date.accessioned	2018-06-14T08:52:20Z
dc.date.available	2018-06-14T08:52:20Z
dc.date.issued	2012-10
dc.identifier.issn	2278-7461
dc.identifier.uri	http://hdl.handle.net/123456789/2017
dc.description	International Journal of Engineering Inventions ISSN: 2278-7461, www.ijeijournal.com Volume 1, Issue 8 (October2012) PP: 07-13	en_US
dc.description.abstract	This paper presents an Artificial Neural Networks (ANN) model for the cost optimization of simply supported beams designed according to the requirements of the ACI 318-08 code. The model formulation includes the cost of concrete, the cost of reinforcement and the cost of formwork. A simply supported beam was designed adopting variable cross sections, in order to demonstrate the model capabilities in optimizing the beam design. Computer models have been developed for the structural design optimization of reinforced concrete simple beams using NEURO SHELL-2 software. The results obtained were compared with the results obtained by using the classical optimization model, developed in the well known Excel software spreadsheet which uses the generalized reduced gradient (GRG). The results obtained using the two modes are in good agreement	en_US
dc.language.iso	en	en_US
dc.publisher	International Journal of Engineering Inventions, Volume 1, Issue 8 (October2012) PP: 07-13	en_US
dc.subject	Reinforced Concrete Beam	en_US
dc.subject	Cost Optimization	en_US
dc.subject	Artificial Neural Networks	en_US
dc.subject	Generalized Reduced Gradient	en_US
dc.title	DESIGN OPTIMIZATION OF REINFORCED CONCRETE BEAMS USING ARTIFICIAL NEURAL NETWORK	en_US
dc.type	Article	en_US