Increasing fuzzy rules cooperation based on evolutionary adaptive inference systems: Research Articles

Authors:
Jesús Alcalá-Fdez;Francisco Herrera;Francisco Márquez;Antonio Peregrín
Affiliations:
Department of Computer Science and Artificial Intelligence, University of Granada, 18071—Granada, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, 18071—Granada, Spain;Department of Electronic Engineering and Automatics, University of Huelva, 21071—Huelva, Spain;Department of Electronic Engineering and Automatics, University of Huelva, 21071—Huelva, Spain
Venue:
International Journal of Intelligent Systems
Year:
2007

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Abstract

This article presents a study on the use of parametrized operators in the Inference System of linguistic fuzzy systems adapted by evolutionary algorithms, for achieving better cooperation among fuzzy rules. This approach produces a kind of rule cooperation by means of the inference system, increasing the accuracy of the fuzzy system without losing its interpretability. We study the different alternatives for introducing parameters in the Inference System and analyze their interpretation and how they affect the rest of the components of the fuzzy system. We take into account three applications in order to analyze their accuracy in practice. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1035–1064, 2007.