Improved knowledge-based neural network (KBNN) model for predicting spring-back angles in metal sheet bending

• Published in: International journal of modeling, simulation and scientific computing Vol. 5; no. 2; p. 1350026
• Main Authors: Bui, Tinh Quoc, Tran, Anh Viet, Shah, Abid Ali
• Format: Journal Article
• Language: English
• Published: Hackensack World Scientific Publishing Company 01.06.2014; World Scientific Publishing Co. Pte., Ltd
• Subjects: Artificial neural networks; Empirical analysis; Finite element method; Knowledge base; Knowledge management; Mathematical models; Metal sheets; Multilayer perceptrons; Neural networks; Process parameters; Response surface methodology; Uranium; genetic algorithm; optimization algorithm; spring-back angles; knowledge-based neural network; Metal sheet bending

We develop an efficiently improved knowledge-based neural network (KBNN) associated with optimization algorithms and finite element analysis (FEA) to accurately predict spring-back angles in metal sheet bending. The well-known V and U prevalent processes of bending are considered. The KBNN predictiv...