Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks
Joint Authors
Bin Mohd, Sabarudin
Keong, Choong Kok
Kamyab Moghadas, R.
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-20
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks.
The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures.
In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm.
Then, radial basis function (RBF) and generalized regression (GR) neural networks are trained to predict the optimal design and maximum deflection of the structures.
The numerical results demonstrate the efficiency of the proposed methodology.
American Psychological Association (APA)
Kamyab Moghadas, R.& Keong, Choong Kok& Bin Mohd, Sabarudin. 2012. Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-1029723
Modern Language Association (MLA)
Kamyab Moghadas, R.…[et al.]. Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks. Mathematical Problems in Engineering No. 2012 (2012), pp.1-18.
https://search.emarefa.net/detail/BIM-1029723
American Medical Association (AMA)
Kamyab Moghadas, R.& Keong, Choong Kok& Bin Mohd, Sabarudin. Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-1029723
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029723