Industrial applications of soft computing: a review

Author

Dote, Yasuhiko ; Ovaska, Seppo J.

Author_Institution

Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Hokkaido, Japan

Volume

89

Issue

9

fYear

2001

fDate

9/1/2001 12:00:00 AM

Firstpage

1243

Lastpage

1265

Abstract

Fuzzy logic, neural networks, and evolutionary computation are the core methodologies of soft computing (SC). SC is causing a paradigm shift in engineering and science fields since it can solve problems that have not been able to be solved by traditional analytic methods. In addition, SC yields rich knowledge representation, flexible knowledge acquisition, and flexible knowledge processing, which enable intelligent systems to be constructed at low cost. This paper reviews applications of SC in several industrial fields to show the various innovations by TR, HMIQ, and low cost in industries that have been made possible by the use of SC. Our paper intends to remove the gap between theory and practice and attempts to learn how to apply soft computing practically to industrial systems from examples/analogy, reviewing many application papers

Keywords

evolutionary computation; fuzzy logic; knowledge acquisition; knowledge representation; manufacturing data processing; neural nets; chaos computing; evolutionary computation; fuzzy logic; industrial systems; intelligent systems; knowledge acquisition; knowledge representation; neural networks; soft computing; Computer applications; Computer industry; Computer networks; Costs; Evolutionary computation; Fuzzy logic; Intelligent systems; Knowledge acquisition; Knowledge representation; Neural networks;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.949483

Filename

949483