A hybrid computing scheme for forward and reverse mappings of metal inert gas welding process Online publication date: Thu, 26-Aug-2010
by Somak Datta, Dilip Kumar Pratihar
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 1, No. 3, 2010
Abstract: A hybrid computing scheme has been developed for carrying out forward and reverse mappings of metal inert gas welding process. As the input-output relationships of this process may not be the same over the entire range of the variables, the mappings have been done using the clusters made by the data points. Optimisation has been carried out to improve the performances of both fuzzy clustering techniques as well as radial basis function neural network used for the clustering and reasoning, respectively. Two approaches of hybrid computing scheme have been proposed, in which a binary-coded genetic algorithm has been utilised to decide the optimal structure of the network (through clustering of the data using two different approaches separately) and a back-propagation algorithm has been employed to determine the optimised parameters of the network. The hybrid scheme has yielded better performance compared to that developed using the genetic algorithm only.
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