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A. Lavaei, A. Lohrasbi, "Dynamic Optimization of Structures subject to Earthquakes", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 19, 2015. doi:10.4203/ccp.109.19

Keywords: optimization, genetic algorithm, earthquake, neural networks, self-organizing map, radial basis function.

Summary

To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting of a self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct radial basis function neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A seventy-two bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

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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: 109 PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping Paper 19 Dynamic Optimization of Structures subject to Earthquakes A. Lavaei and A. Lohrasbi Department of Civil Engineering, College of Engineering, Boroujerd Branch, Islamic Azad University, Iran doi:10.4203/ccp.109.19 purchase the full-text of this paper Full Bibliographic Reference for this paper A. Lavaei, A. Lohrasbi, "Dynamic Optimization of Structures subject to Earthquakes", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 19, 2015. doi:10.4203/ccp.109.19 Keywords: optimization, genetic algorithm, earthquake, neural networks, self-organizing map, radial basis function. Summary To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting of a self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct radial basis function neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A seventy-two bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method. 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 £50 +P&P)
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