Artificial Neural Networks (ANNs) as a Novel Modeling Technique in Tribology

Artificial Neural Networks (ANNs) as a Novel Modeling Technique in Tribology

In the present paper, artificial neural networks (ANNs) are considered from a mathematical modeling point of view. A short introduction to feedforward neural networks is outlined, including multilayer perceptrons (MLPs) and radial basis function (RBF) networks. Examples of their applications in trib...

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Bibliographic Details
Main Author: Ivan Argatov
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-05-01
Series:Frontiers in Mechanical Engineering
Subjects:
artificial neural network
data-driven modeling
tribological properties
wear
fretting
Online Access:https://www.frontiersin.org/article/10.3389/fmech.2019.00030/full
Description
Summary:In the present paper, artificial neural networks (ANNs) are considered from a mathematical modeling point of view. A short introduction to feedforward neural networks is outlined, including multilayer perceptrons (MLPs) and radial basis function (RBF) networks. Examples of their applications in tribological studies are given, and important features of the data-driven modeling paradigm are discussed.
ISSN:2297-3079

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