Comparison of different supervised learning algorithms for position analysis of the slider-crank mechanism

Slider-crank mechanisms have a wide range of applications in machine design, primarily for converting rotary motion into reciprocating motion, as seen in internal combustion engines, pumps, compressors, and human-powered vehicles. Due to their widespread usage, analytical and graphical solutions for...

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Veröffentlicht in:	Alexandria engineering journal Jg. 92; S. 39 - 49
1. Verfasser:	Denizhan, Onur
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2024 Elsevier
Schlagworte:	Artificial neural networks Bayesian Regularization Levenberg-Marquardt Backpropagation Position analysis Scaled Conjugate Gradient Descent Slider-crank mechanism Scaled Conjugate Gradient Descent Bayesian Regularization Levenberg-Marquardt Backpropagation Position analysis Slider-crank mechanism Artificial neural networks
ISSN:	1110-0168
Online-Zugang:	Volltext
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