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Activation energy at hot deformation represents a valuable physical quantity which finds its application e.g. in the case of a hot flow stress description. It has been showed that this quantity can be treated as a material constant, strain-dependent variable or even as strain, strain rate and temperature dependent variable. A mathematical description of the last and in the same time the most complicated dependency is the aim of the presented paper. Two mathematically different methodologies have been applied to cope with this issue – a multivariate polynomial relationship and an artificial neural network approach. The results have shown that the neural network approach represents an ideal one although the polynomial one is also applicable.
Keywords: Hot deformation activation energy, multivariate polynomials, artificial neural networks© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.