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

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

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 multila...

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Bibliographic Details
Main Authors: Tomasz Trzepieciński, Hirpa G. Lemu
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Materials
Subjects:
elastic strain
genetic algorithm
material properties
perceptron-based prediction
springback
steel sheet metal
Online Access:https://www.mdpi.com/1996-1944/13/14/3129

Internet

https://www.mdpi.com/1996-1944/13/14/3129

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