Application of Artificial Neural Network in Biotribological Research of Dental Glass Ceramic

A tribological system is a complex non-linear system composed of the elements that are connected structurally and functionally. The aim of this paper is to present an overview of artificial neural networks, its development and applications of neural networks in the prediction of tribological properties of dental glass ceramic using a newly measured ball-on-plate nanotribometer. The possibility of artificial neural networks application to solve complex nonlinear problems and to identify tribological characteristics of dental glass ceramic in terms of wear rate and coefficient of friction is presented