Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/31060
Title: Optimization of silk yarn hierarchical structure by genetic algorithm to design scaffolds
Authors: Naghashzargar, Elham
Semnani, Dariush
Karbasi, Saeed
Keywords: Artificial neural network;Genetic algorithm;Mechanical properties;Scaffolds;Silk;Tissue engineering
Issue Date: Mar-2015
Publisher: NISCAIR-CSIR, India
Abstract: A genetic algorithm model has been developed to determine the optimal parameters of mechanical aspects of a silk wire-rope scaffold with the highest predictive accuracy and generalized ability simultaneously. The study pioneered on employing a genetic algorithm (GA) to optimize the parameters of scaffold in tendon and ligament tissue engineering. Experimental results show that the GA model performs the best predictive accuracy to imply mechanical behavior with native values successfully.
Page(s): 81-86
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.40(1) [March 2015]

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