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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Yong Xu, Xuewei Zhang, Wenlong Xie, Shihong Zhang, Yaqiang Tian, Liansheng Chen
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2025-05-01
Schriftenreihe:Applied Sciences
Schlagworte:
variable diameter tubes
hydroforming
machine learning
GA-PSO-BP algorithm
Online-Zugang:https://www.mdpi.com/2076-3417/15/9/5045
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