Improving Prediction of Springback in Sheet Metal Forming Using Multilayer Perceptron-Based Genetic Algorithm

Volume: 13, Issue: 14, Pages: 3129 - 3129
Published: Jul 14, 2020
Abstract
This paper presents the results of predictions of springback of cold-rolled anisotropic steel sheets using an approach based on a multilayer perceptron-based artificial neural network (ANN) coupled with a genetic algorithm (GA). A GA was used to optimise the number of input parameters of the multilayer perceptron that was trained using different algorithms. In the investigations, the mechanical parameters of sheet material determined in uniaxial...
Paper Details
Title
Improving Prediction of Springback in Sheet Metal Forming Using Multilayer Perceptron-Based Genetic Algorithm
Published Date
Jul 14, 2020
Journal
Volume
13
Issue
14
Pages
3129 - 3129
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