@article{neural-network-intelligence-adr, author = {Akshansh Mishra}, title = { An Artificial Intelligence based Approach to Determine the Elongation % and Ultimate Tensile Strength of Friction Stir Welded Dissimilar Marine Grade Aluminium Alloy Joints}, journal = {Journal of Advanced Research in Applied Artificial Intelligence and Neural Network}, volume = {3}, number = {1}, year = {2021}, keywords = {}, abstract = {Neural networks are a new generation of information processingparadigms designed to mimic some of the behaviours of the humanbrain. These networks have gained tremendous popularity due to theirability to learn, recall and generalize from training data. A number ofneural network paradigms have been reported in the last four decades,and in the last decade the neural networks have been refined and widelyused by researchers and application engineers. This study focuses on theprediction of the elongation % and Ultimate Tensile Strength (UTS) ofthe dissimilar Friction Stir Welded joints of aluminium alloys by trainingthe Neural Network on Quasi Newton Algorithm.How to cite this article:Mishra A, Singh A, Saravanan M et al. An ArtificialIntelligence based Approach to Determine theElongation % and Ultimate Tensile Strength ofFriction Stir Welded Dissimilar Marine GradeAluminium Alloy Joints. J Adv Res Appl Arti IntelNeural Netw 2019; 3(1): 1-21.}, pages = {1--21}, url = {http://www.thejournalshouse.com/index.php/neural-network-intelligence-adr/article/view/372} }