Neural network design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Journal of Intelligent Manufacturing
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This work describes an application of an integrated approach using the Taguchi method (TM), neural network (NN) and genetic algorithm (GA) for optimizing the lap joint quality of aluminum pipe and flange in automotive industry. The proposed approach (Taguchi-Neural-Genetic approach) consists of two phases. In first phase, the TM was adopted to collect training data samples for the NN. In second phase, a NN with a Levenberg-Marquardt back-propagation (LMBP) algorithm was adopted to develop the relationship between factors and the response. Then, a GA based on a well-trained NN model was applied to determine the optimal factor settings. Experimental results illustrated the Taguchi-Neural-Genetic approach.