Mechanical Sciences
Mechanical Sciences
Mechanical Sciences
Articles | Volume 12, issue 2
Articles | Volume 12, issue 2
https://doi.org/10.5194/ms-12-777-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ms-12-777-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 12, issue 2
Research article
 | 
09 Aug 2021
Research article |  | 09 Aug 2021

Prediction of springback in local bending of hull plates using an optimized backpropagation neural network

Binjiang Xu, Lei Li, Zhao Wang, Honggen Zhou, and Di Liu

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Latest update: 20 Nov 2024
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Short summary
Springback is an inevitable problem in the local bending process of hull plates, which leads to low processing efficiency and affects the assembly accuracy. Therefore, the prediction of the springback effect, as a result of the local bending of hull plates, bears great significance. In total, four springback prediction models, based on genetic and back propagation neural network (GA-BPNN) algorithms and the improved particle swarm optimization (PSO)-BPNN algorithms, are established.
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