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Neural Computing and Applications

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01.07.2013 | Original Article

RETRACTED ARTICLE: Modeling hardness of Nb-microalloyed steels using fuzzy logic

verfasst von: Gholamreza Khalaj, Hossein Yoozbashizadeh, Alireza Khodabandeh, Ali Nazari

Erschienen in: Neural Computing and Applications | Ausgabe 1/2013

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Abstract

The paper presents some results of the research connected with the development of new approach based on the fuzzy logic of predicting the Vickers microhardness of the phase constituents occurring in five steels after continuous cooling. The independent variables in the model are chemical compositions, initial austenite grain size, and cooling rate over the temperature range of the occurrence of phase transformations. For purpose of constructing these models, 114 different experimental data were gathered from the literature. The data used in the fuzzy logic model are arranged in a format of twelve input parameters that cover the chemical compositions, initial austenite grain size, and cooling rate, and output parameter which is Vickers microhardness. In this model, the training and testing results in the fuzzy logic systems have shown strong potential for prediction of effects of chemical compositions and heat treatments on hardness of microalloyed steels.

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Titel: RETRACTED ARTICLE: Modeling hardness of Nb-microalloyed steels using fuzzy logic
verfasst von: Gholamreza Khalaj
Hossein Yoozbashizadeh
Alireza Khodabandeh
Ali Nazari
Publikationsdatum: 01.07.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 1/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-011-0802-4

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