Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/xmlui/handle/10054/4682
Title: A genetic algorithm and gradient-descent-based neural network with the predictive power of a heat and fluid flow model for welding
Authors: MISHRA, S
DEBROY, T
Keywords: 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
Issue Date: 2006
Publisher: AMER WELDING SOC
Citation: WELDING JOURNAL, 85(11), 231S-242S
Abstract: 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.
URI: http://dspace.library.iitb.ac.in/xmlui/handle/10054/4682
http://hdl.handle.net/10054/4682
ISSN: 0043-2296
Appears in Collections:Article

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.