@ARTICLE{Perec2024:i8133,
	author="{Perec, Andrzej and Kawecka, Elżbieta}",
	title="{Modeling of the Abrasive Water Jet machining by ANN in uncertainty conditions}",
	year="2024",
	type="artykuł naukowy / referat",
	language="en",
	journal="{Procedia Computer Science}",
	issn="1877-0509",
	volume="246",
	pages="2176--2184",
	doi="10.1016/j.procs.2024.09.607",
	url="https://www.sciencedirect.com/science/article/pii/S1877050924026590",
	keywords="cutting efficiency; abrasive water jet; artificial neural network; modeling",
	abstract="{This article presents the using of artificial neural networks in modeling of abrasive water jet (AWJ) cut process of brass. Three-ply layer perceptron type network with an error Broyden - Fletcher - Goldfarb - Shanno (BFGS) learning algorithm was applied to modeling this process. The paper provides detailed description of used neural network. This neural network simulates the machining process end influence of control parameters as abrasive grain size, nozzle ID, abrasive flow and traverse speed on cutting efficiency under given parameters. The results were comparison with the laboratory results of complex studies on parameters of brass cutting by AWJ.}",
}