Design of neural networks model for transmission angle of a modified mechanism
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, vol.19, no.10, pp.1875-1884, 2005 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 19 Issue: 10
- Publication Date: 2005
- Doi Number: 10.1007/bf02984266
- Journal Name: JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.1875-1884
- Erciyes University Affiliated: Yes
Abstract
This paper discusses Neural Networks as predictor for analyzing of transmission angle of slider-crank mechanism. There are different types of neural network algorithms obtained by using chain rules. The neural network is a feedforward neural network. On the other hand, the slider-crank mechanism is a modified mechanism by using an additional link between connecting rod and crank pin. Through extensive simulations, these neural network models are shown to be effective for prediction and analyzing of a modified slider-crank mechanism’s transmission angle.
This paper discusses Neural Networks as predictor for analyzing of transmission angle of slider-crank mechanism. There are different types of neural network algorithms obtained by using chain rules. The neural network is a feedforward neural network. On the other hand, the slider-crank mechanism is a modified mechanism by using an additional link between connecting rod and crank pin. Through extensive simulations, these neural network models are shown to be effective for prediction and analyzing of a modified slider-crank mechanism's transmission angle.