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Indian Journal of Engineering and Materials Sciences (IJEMS) >
IJEMS Vol.13 [2006] >
IJEMS Vol.13(6) [December 2006] >
| Title: | Optimized column design using genetic algorithm based neural networks |
| Authors: | Rao, H Sudarsana
Babu, B Ramesh |
| Issue Date: | Dec-2006 |
| Publisher: | CSIR |
| IPC Code: | E04C3/30
G06N3/02 |
| Abstract: | In the structural
design of columns, the dimensions of the column and reinforcement are initially
assumed and then the interaction formula is used to verify the suitability of
chosen dimensions and reinforcement. This approach necessitates few trials for
coming up with an economical and safe design. This paper demonstrates the
applicability of artificial neural networks (ANN) and genetic algorithms (GA)
for the design of short columns under biaxial bending. A hybrid neural network
model that combines the features of feed forward neural networks and genetic
algorithms has been developed for the design of short column subjected to
biaxial bending. The network has been trained with design data obtained from
design experts in the field. The hybrid neural network model learned the design
of column in just 1800 training cycles. After successful learning, the model
predicted the percentage of steel required for new problems with good accuracy
satisfying all design constraints. The results of the hybrid network model are
compared with the solution of an optimizer, which uses the interior penalty
function method. The various stages involved in the development of genetic
algorithm based neural network model are addressed. |
| Page(s): | 503-511 |
| ISSN: | 0975-1017 (Online); 0971-4588 (Print) |
| Source: | IJEMS Vol.13(6) [December 2006]
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