A genetic algorithm and gradient-descent-based neural network with the predictive power of a heat and fluid flow model for welding
DSpace at IIT Bombay
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Title |
A genetic algorithm and gradient-descent-based neural network with the predictive power of a heat and fluid flow model for welding
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Creator |
MISHRA, S
DEBROY, T |
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Subject |
steel arc welds
ferrite number prediction alloy shipbuilding steels monte-carlo-simulation multivariable optimization improving reliability back-propagation ti-6al-4v welds complex joints affected zone neural networks gas tungsten are welding (gtaw) heat transfer and fluid flow model low-carbon steel |
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Description |
Six neural networks were developed for gas tungsten arc welding of low-carbon steel, with each network providing one of the six output parameters of G TA welds.
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Publisher |
AMER WELDING SOC
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Date |
2011-07-17T09:06:05Z
2011-12-26T12:50:13Z 2011-12-27T05:36:21Z 2011-07-17T09:06:05Z 2011-12-26T12:50:13Z 2011-12-27T05:36:21Z 2006 |
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Type |
Article
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Identifier |
WELDING JOURNAL, 85(11), 231S-242S
0043-2296 http://dspace.library.iitb.ac.in/xmlui/handle/10054/4682 http://hdl.handle.net/10054/4682 |
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Language |
en
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