Improving prediction of springback in sheet metal forming using multilayer perceptron-based

HIGHLIGHTS

• who: Genetic, Algorithm and Tomasz, Trzepieciński from the Department of Materials Forming and Processing, Rzeszow University of Technology, alPowst have published the research: Improving Prediction of Springback in Sheet Metal Forming Using Multilayer Perceptron-Based, in the Journal: Materials 2020, 13, x FOR PEER REVIEW of /2020/
• what: 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 (GA). In the investigations the mechanical parameters of sheet material determined in uniaxial tensile tests . . .
  

   

  

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