Determination of selected characteristics of steels, based on the type of the CCT diagram, using artificial neural networks

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Determination of selected characteristics of steels, based on the type of the CCT diagram, using artificial neural networks

Bogdan Pawłowski, Paweł Popowicz

AGH University of Science and Technology.

DOI:

https://doi.org/10.7494/cmms.2002.1.0019

Abstract:

The paper focuses on classification of steels using the artificial neural network (ANN) approach. The steels are grouped into classes according to the Wever and Rose TTT diagrams. It is also shown that the accuracy of ANN predictions of some characteristics of steels (critical temperatures Ac3) can be improved if the ANN learning data, based on the chemical compositions of steels, are initially arranged into different types of TTT diagrams.

Cite as:

Pawłowski, B., Popowicz, P. (2002). Determination of selected characteristics of steels, based on the type of the CCT diagram, using artificial neural networks. Computer Methods in Materials Science, 2(1), 19 – 25. https://doi.org/10.7494/cmms.2002.1.0019

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Keywords:

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