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Paper IV.6

A Neural Network Model to Study the Effect of Building Configuration on the Seismic Response

S.A. Mourad*, A.W. Sadek* and T.M. Mohamed+

*Faculty of Engineering, Cairo University, Egypt
+Building Research Centre, Cairo, Egypt

doi:10.4203/ccp.53.4.6

S.A. Mourad, A.W. Sadek, T.M. Mohamed, "A Neural Network Model to Study the Effect of Building Configuration on the Seismic Response", in B.H.V. Topping, (Editor), "Advances in Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, pp 199-205, 1998. doi:10.4203/ccp.53.4.6

Abstract

Neural networks have demonstrated versatility as a problem solving tool with various applications in engineering problems. A neural network model is investigated for studying the effect of building irregularities on the seismic response. Different network topologies were tested to solve the problem. Input parameters for each network defined the building configuration whereas the output defined the increase in stresses as compared to a reference (regular) structure. The networks were trained with the output produced from dynamic analysis of the structures based on finite-element models. The network topology that produced the best results in both training and testing processes was identified.

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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: 53 ADVANCES IN ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping Paper IV.6 A Neural Network Model to Study the Effect of Building Configuration on the Seismic Response S.A. Mourad, A.W. Sadek and T.M. Mohamed+ *Faculty of Engineering, Cairo University, Egypt +Building Research Centre, Cairo, Egypt doi:10.4203/ccp.53.4.6 purchase the full-text of this paper Full Bibliographic Reference for this paper S.A. Mourad, A.W. Sadek, T.M. Mohamed, "A Neural Network Model to Study the Effect of Building Configuration on the Seismic Response", in B.H.V. Topping, (Editor), "Advances in Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, pp 199-205, 1998. doi:10.4203/ccp.53.4.6 Abstract Neural networks have demonstrated versatility as a problem solving tool with various applications in engineering problems. A neural network model is investigated for studying the effect of building irregularities on the seismic response. Different network topologies were tested to solve the problem. Input parameters for each network defined the building configuration whereas the output defined the increase in stresses as compared to a reference (regular) structure. The networks were trained with the output produced from dynamic analysis of the structures based on finite-element models. The network topology that produced the best results in both training and testing processes was identified. 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 £75 +P&P)
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