Introduction to Grey system theory
The Journal of Grey System
Neural network design
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
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The objective of this paper is to present an integrated approach using the Taguchi method (TM), grey relational analysis (GRA) and a neural network (NN) to optimize the weld bead geometry in a novel gas metal arc (GMA) welding process. The TM is first used to construct a database for the NN. The GRA is adopted to solve the problem of multiple performance characteristics in a GMA welding process using activating flux. The grey relational grade obtained from the GRA is used as the output of the back-propagation (BP) NN. Then, a NN with the Levenberg-Marquardt BP (LMBP) algorithm is used to provide the nonlinear relationship between welding parameters and grey relational grade of each weldment. The optimal parameters of the novel GMA welding process were determined by simulating parameters using a well-trained BPNN model. Experimental results illustrate the proposed approach.