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W.M. Jenkins, "Neural Network-Based Approximations for Structural Analysis", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 25-35, 1995. doi:10.4203/ccp.34.2.1

Abstract

Structural design optimization involves, coincidentally, the continuous re-analysis of the structure in line with changes in topology and structural properties. If the re-analysis is carried out by exact methods. then the CPU time needed for the optimization can be significantly increased. In these circumstances, approximate methods may offer an alternative to exact re-analysis. There are other situations where access to a reliable and rapid approximate analysis would be an advantage. for example with highly standardized or regular structures. This paper describes a study of the application of a neural network-based method of approximate analysis and offers some observations on matters such as network topology and training.

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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: 34 DEVELOPMENTS IN NEURAL NETWORKS AND EVOLUTIONARY COMPUTING FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping Paper II.1 Neural Network-Based Approximations for Structural Analysis W.M. Jenkins Department of Civil Engineering, University of Leeds, Leeds, UK doi:10.4203/ccp.34.2.1 purchase the full-text of this paper Full Bibliographic Reference for this paper W.M. Jenkins, "Neural Network-Based Approximations for Structural Analysis", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 25-35, 1995. doi:10.4203/ccp.34.2.1 Abstract Structural design optimization involves, coincidentally, the continuous re-analysis of the structure in line with changes in topology and structural properties. If the re-analysis is carried out by exact methods. then the CPU time needed for the optimization can be significantly increased. In these circumstances, approximate methods may offer an alternative to exact re-analysis. There are other situations where access to a reliable and rapid approximate analysis would be an advantage. for example with highly standardized or regular structures. This paper describes a study of the application of a neural network-based method of approximate analysis and offers some observations on matters such as network topology and training. 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 £55 +P&P)
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