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Extraction of knowledge from high strength steel data using soft computing techniques—an overview
Author(s) -
Datta Shubhabrata
Publication year - 2009
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.10024
Subject(s) - soft computing , artificial neural network , fuzzy logic , computer science , knowledge extraction , data mining , artificial intelligence
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