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A. Arslan, R. Ince, "A Neural Network-Based Design of Edge Supported R.C. Slabs", in B.H.V. Topping, M. Papadrakakis, (Editors), "Artificial Intelligence and Object Oriented Approaches to Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 91-97, 1994. doi:10.4203/ccp.27.2.3

Abstract

Modeling of material behavior generally involves the development of mathematical model derived from observations and experimental data. An alternative way discussed in this paper, is neural network based modeling that a subfield of artificial intelligence. The main benefit in using a neural network approach is that the network is built directly from experimental or theoretical data using the self organizing capabilities of the neural network.

In this article, a back-propagation neural network package (NETICE) was presented which has been developed for use in general purpose. NETICE (Neural nETworks In Civil Engineering) has been used in the design of edge supported reinforced concrete slabs and the results were presented in this study. It has been observed that the results given by the network has a high approximation when compared with the conventional solution.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 27 ARTIFICIAL INTELLIGENCE AND OBJECT ORIENTED APPROACHES TO STRUCTURAL ENGINEERING Edited by: B.H.V. Topping and M. Papadrakakis Paper II.3 A Neural Network-Based Design of Edge Supported R.C. Slabs A. Arslan and R. Ince Civil Engineering Department, Firat University, Elazig, Turkey doi:10.4203/ccp.27.2.3 purchase the full-text of this paper Full Bibliographic Reference for this paper A. Arslan, R. Ince, "A Neural Network-Based Design of Edge Supported R.C. Slabs", in B.H.V. Topping, M. Papadrakakis, (Editors), "Artificial Intelligence and Object Oriented Approaches to Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 91-97, 1994. doi:10.4203/ccp.27.2.3 Abstract Modeling of material behavior generally involves the development of mathematical model derived from observations and experimental data. An alternative way discussed in this paper, is neural network based modeling that a subfield of artificial intelligence. The main benefit in using a neural network approach is that the network is built directly from experimental or theoretical data using the self organizing capabilities of the neural network. In this article, a back-propagation neural network package (NETICE) was presented which has been developed for use in general purpose. NETICE (Neural nETworks In Civil Engineering) has been used in the design of edge supported reinforced concrete slabs and the results were presented in this study. It has been observed that the results given by the network has a high approximation when compared with the conventional solution. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £45 +P&P)
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