Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning

Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning

To predict the forming behaviour of aluminium alloy variable diameter tubes during hydroforming, a genetic algorithm-enhanced particle swarm optimisation (GA-PSO) is used to optimise a backpropagation neural network (BP-NN). A fast prediction model based on the GA-PSO-BP neural network for the hydro...

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Bibliographic Details
Main Authors: Yong Xu, Xuewei Zhang, Wenlong Xie, Shihong Zhang, Yaqiang Tian, Liansheng Chen
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
variable diameter tubes
hydroforming
machine learning
GA-PSO-BP algorithm
Online Access:https://www.mdpi.com/2076-3417/15/9/5045
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