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Hybrid intelligent systems for industrial data analysis
Author(s) -
Kordon Arthur K.
Publication year - 2004
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10169
Subject(s) - computer science , genetic programming , generalization , key (lock) , support vector machine , artificial neural network , artificial intelligence , machine learning , data mining , computational intelligence , industrial engineering , engineering , mathematical analysis , mathematics , computer security
A novel approach for industrial data analysis based on integration of three key computational intelligence approaches—genetic programming (GP), analytical neural networks, and support vector machines (SVMs)—is proposed. The developed empirical models have good generalization capabilities, explicit input/output relationships, self‐assessment capabilities, and low implementation and maintenance cost. The proposed approach has been implemented in several industrial applications in The Dow Chemical Company. © 2004 Wiley Periodicals, Inc.