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Neural networks are a new generation of information processing paradigms designed to mimic some of the behaviours of the human brain. These networks have gained tremendous popularity due to their ability to learn, recall and generalize from training data. A number of neural network paradigms have been reported in the last four decades, and in the last decade the neural networks have been refined and widely used by researchers and application engineers. This study focuses on the prediction of the elongation % and Ultimate Tensile Strength (UTS) of the dissimilar Friction Stir Welded joints of aluminium alloys by training the Neural Network on Quasi Newton Algorithm. How to cite this article Mishra A, Singh A, Saravanan M et al. An Artificial Intelligence based Approach to Determine the Elongation % and Ultimate Tensile Strength of Friction Stir Welded Dissimilar Marine Grade Aluminium Alloy Joints. J Adv Res Appl Arti Intel Neural Netw 2019; 3(1&2): 1-21.

south asian research journal of engineering and technology

An Artificial Intelligence Based Approach to Determine the Elongation % and Ultimate Tensile Strength of Friction Stir Welded Dissimilar Marine Grade Aluminium Alloy Joints