In the present paper, artificial neural networks (ANNs) are considered from a mathematical modelling 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 modelling paradigm are discussed.
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Ivan Argatov (2019) studied this question.
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