Neural networks committee decision making for estimation of metal’s hardness properties from indentation data

Abstract

In this paper the problem of metal’s hardness properties estimation from indentation data is concerned. This problem belongs to a class of ill-posed vector function approximation problems and can’t be solved by a single multilayered perceptron at the required precision level. A special neural networks committee architecture is developed in order to obtain… (More)
DOI: 10.3103/S1060992X11020081

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