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P. Zeng, "Artificial Neural Network Computing in Structural Engineering", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 37-50, 1995. doi:10.4203/ccp.34.2.2

Abstract

The paper studies artificial neural network (ANN) computing for structural analysis, which covers neurons element for structural analysis, networks for structural analysis, mathematical principle, implementation procedure, simulating method on the present digital computer. Research shows that ANN computing inherently has many attractive features such as massively parallel distributed processing, continuous dynamics and collective computational capabilities, which will be especially appropriate to structural analysis. The results of numerical simulations on 4-bar truss, 7-bar truss, 15-bar truss, beam structure, as well as planar continuous structure are presented to confirm ANN computing. The results also show the convergence speed of ANN computing does not closely depend on the computational scales of the original problems, which can arrive at the order of magnitude of 1*10^-9 seconds.

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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.2 Artificial Neural Network Computing in Structural Engineering P. Zeng Institute B of Mechanics, University of Stuttgart, Stuttgart, Germany doi:10.4203/ccp.34.2.2 purchase the full-text of this paper Full Bibliographic Reference for this paper P. Zeng, "Artificial Neural Network Computing in Structural Engineering", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 37-50, 1995. doi:10.4203/ccp.34.2.2 Abstract The paper studies artificial neural network (ANN) computing for structural analysis, which covers neurons element for structural analysis, networks for structural analysis, mathematical principle, implementation procedure, simulating method on the present digital computer. Research shows that ANN computing inherently has many attractive features such as massively parallel distributed processing, continuous dynamics and collective computational capabilities, which will be especially appropriate to structural analysis. The results of numerical simulations on 4-bar truss, 7-bar truss, 15-bar truss, beam structure, as well as planar continuous structure are presented to confirm ANN computing. The results also show the convergence speed of ANN computing does not closely depend on the computational scales of the original problems, which can arrive at the order of magnitude of 1*10^-9 seconds. 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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