Coherence of radial implicative fuzzy systems with nominal consequents

• Autorzy: Poufal D.
• Języki publikacji: EN

Abstrakty

EN

In the paper we are interested in the question of coherence of radial implicative fuzzy systems with nominal consequents (radial I-FSs with NCs). Implicative fuzzy systems are fuzzy systems employing residuated fuzzy implications for representation of IF-THEN structure of their rules. Radial fuzzy systems are fuzzy systems exhibiting the radial property in antecedents of their rules. The property simplifies computational model of radial systems and makes the investigation of their properties more tractable. A fuzzy system has nominal consequents if its output is defined on a finite unordered set of possible actions which are generally quantitatively incomparable. The question of coherence is the question of under which conditions we are assured that regardless the input to the system is, an output of the system exists, i.e., the output is non-empty. In other words, a fuzzy system is coherent if it has no contradictory rules in its rule base. In the paper we state sufficient conditions for a radial I-FS with NCs to be coherent.

Słowa kluczowe

EN

implicative fuzzy system; radial fuzzy system; nominal output space; coherence

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2006
• Tom: nr 4
• Strony: 60--66
• Opis fizyczny: Bibliogr. 9 poz., tab.

Twórcy

autor

Poufal D.

• Institute of Computer Science AS CR, Pod Vod´arenskou vˇeˇz´i 2, 182 07 Prague 8, Czech Republic,

Bibliografia

• [1] D. Coufal, “Representation of continuous Archimedean radial fuzzy systems”, in Proc. IFSA 2005 World Congr., Beijing, China, 2005, pp. 1174–1179.
• [2] D. Coufal, “Radial implicative fuzzy inference systems”, Ph.D. thesis, University of Pardubice, Czech Republic, 2003, http://www.cs.cas.cz/∼coufal/thesis
• [3] D. Dubois and H. Prade, “What are fuzzy rules and how to use them?”, Fuzzy Sets Syst., vol. 84, no. 2, pp. 169–185, 1996.
• [4] D. Dubois, H. Prade, and L. Ughetto, “Checking the coherence and redundancy of fuzzy knowledge bases”, IEEE Trans. Fuzzy Syst., vol. 5, no. 3, pp. 398–417, 1997.
• [5] A. Friedman, Foundations of Modern Analysis. New York: Dover Publ., 1982.
• [6] P. Hájek, Metamathematics of Fuzzy Logic. Dordrecht: Kluwer, 1998.
• [7] G. J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic – Theory and Applications. Upper Saddle River: Prentice Hall, 1995.
• [8] L. X. Wang, A Course in Fuzzy Systems and Control. Upper Saddle River: Prentice Hall, 1997.
• [9] R. R. Yager and L. Larsen, “On discovering potential inconsistencies in validating uncertain knowledge bases by reflecting on the input”, IEEE Trans. Syst., Man Cybern., vol. 21, no. 4, pp. 790–801, 1991.