Modeling and process parameter optimization of laser cutting based on artificial neural network and intelligent optimization algorithm

Laser cutting technology has proven advantageous in processing high-hardness metals, ceramics, and composites. However, the process parameters significantly influence the kerf and heat-affected zone widths. Therefore, it is necessary to establish an accurate prediction model of laser cutting quality...

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Vydané v:	International journal of advanced manufacturing technology Ročník 127; číslo 3-4; s. 1177 - 1188
Hlavní autori:	Ren, Xingfei, Fan, Jinwei, Pan, Ri, Sun, Kun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.07.2023 Springer Nature B.V
Predmet:	Artificial neural networks CAE) and Design Computer-Aided Engineering (CAD Efficiency Engineering Genetic algorithms Heat affected zone Industrial and Production Engineering Kerf Laser beam cutting Lasers Machining Mathematical models Mechanical Engineering Media Management Neural networks Optimization algorithms Original Article Particle swarm optimization Prediction models Process parameters Sorting algorithms Laser cutting Artificial neural network Particle swarm optimization Heat-affected zone Machining process modeling
ISSN:	0268-3768, 1433-3015
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