Neural Network Approaches to Aid Simple Truss Design Problems |
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Authors: | Hyeong-Taek Kang C John Yoon |
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Affiliation: | Department of Civil and Environmental Engineering, Polytechnic University, Six Metrotech Center, Brooklyn, New York, 11201, USA |
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Abstract: | Abstract: Diverse problems in engineering may be solved accurately with computers. In structural engineering, many solution techniques exist. Over the past few years, neural networks have evolved as a new computing paradigm, and many engineering applications have been studied. This paper describes configuring and training of a neural network for a truss design application and explores the possible roles for neural networks in structural design problems. The specific problem considered is a simple truss design where, given a geometry and a loading, economical cross-sectional areas of all the members are to be selected. For this problem, a two-layer neural network is trained using the back-propagation algorithm with patterns representing optimal designs for diverse loading conditions. The performance of the trained neural network is evaluated with a sample problem. |
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