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Comparison of New Formulations for Martensite Start Temperature of Fe-Mn-Si Shape Memory Alloys Using Geneting Programming and Neural Networks

Computers, Materials & Continua 2009, 10(1), 65-96. https://doi.org/10.3970/cmc.2009.010.065

Abstract

This work proposed an alternative formulation for the prediction of martensite start temperature (Ms) of Fe-Mn-Si shape memory alloys (SMAs) depending on the various compositions and heat treatment techniques by using Neural Network (NN) and genetic programming (GP) soft computing techniques. The training and testing patterns of the proposed NN and GP formulations are based on well established experimental results from the literature. The NN and GP based formulation results are compared with experimental results and found to be quite reliable with a very high correlation (R2=0.955 for GEP and 0.999 for NN).

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APA Style
(2009). Comparison of new formulations for martensite start temperature of fe-mn-si shape memory alloys using geneting programming and neural networks. Computers, Materials & Continua, 10(1), 65-96. https://doi.org/10.3970/cmc.2009.010.065
Vancouver Style
. Comparison of new formulations for martensite start temperature of fe-mn-si shape memory alloys using geneting programming and neural networks. Comput Mater Contin. 2009;10(1):65-96 https://doi.org/10.3970/cmc.2009.010.065
IEEE Style
et al., "Comparison of New Formulations for Martensite Start Temperature of Fe-Mn-Si Shape Memory Alloys Using Geneting Programming and Neural Networks," Comput. Mater. Contin., vol. 10, no. 1, pp. 65-96. 2009. https://doi.org/10.3970/cmc.2009.010.065



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