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Extraction of knowledge from high strength steel data using soft computing techniques—an overview

Authors

  • Shubhabrata Datta

    Corresponding author
    1. School of Materials Science and Engineering, Bengal Engineering and Science University, Shibpur, Howrah 711 103, India
    • School of Materials Science and Engineering, Bengal Engineering and Science University, Shibpur, Howrah 711 103, India
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Abstract

Soft computing techniques like artificial neural network, fuzzy logic and genetic algorithm are used to extract knowledge from experimentally developed data on the mechanical properties of thermomechanically processed high-strength steel. Though these techniques, in most case, are used for developing models or optimizing a system, here the additional factor of gathering better understanding of the steel system, under investigation, has also been targeted. The extracted information has been validated by the existing concepts of physical metallurgy of steel. It is seen that these tools have the capability to confirm some of the hypotheses generated through experimentation and could easily be utilized for designing the steel with superior and/or tailor-made properties. Copyright © 2009 Wiley Periodicals, Inc., A Wiley Company

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