Genetic tuning fuzzy dempster-shafer decision rules

• Autorzy: Walijewski J. S. , Sosnowski Z. A.
• Języki publikacji: EN

Abstrakty

EN

The objective of this paper is to employ the Dempster-Shafer theory (DST) as a vehicle supporting the generation of fuzzy decision rules. The concept of fuzzy granulation realized via fuzzy clustering is aimed at the discretization of continuous attributes. Next we use Genetic for tuning fuzzy decision rules. Detailed experimental studies are presented concerning well-known medical data sets available on the Web.

Słowa kluczowe

EN

genetic algorithms; fuzzy modelling; Dempster-Shafer theory

• Wydawca: Politechnika Gdańska
• Czasopismo: TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk
• Rocznik: 2002
• Tom: Vol. 6, No 4
• Strony: 631--640
• Opis fizyczny: Bibliogr. 9 poz., rys., tab.

Twórcy

autor

Walijewski J. S.

• Department of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351 Białystok, Poland

autor

Sosnowski Z. A.

• Department of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351 Białystok, Poland

Bibliografia

• [1] Sosnowski Z A and Walijewski J S 1999 Proc. 13th European Simulation Multiconference, Warsaw, Poland, p. 419
• [2] Sosnowski Z A and Walijewski J S Proc. 7th Workshop of the Polish Society of Computer Simulation, Zakopane, Poland, p. 273
• [3] Bianaghi E and Madella P 1997 Proc. 7th IFSA World Congress, Prague, Czech Republic, 1 197
• [4] Bezdek J C, Sabin M J and Tucker W T 1987 IEEE Trans. On System, Man and Cybernetics 17 (5) 873
• [5] http://www.ics.uci.edu/mlearn/MLRepository.html
• [6] Hunter A 1995 SUGAL Genetic Algorithm Simulator, University of Sunderland, UK
• [7] Pedrycz W and Sosnowski Z A 2000 IEEE Trans, on Systems, Man and Cybernetics A 30 151
• [8] Quinlann J R 1986 Machine Learning 1 81
• [9] Weber R 1992 Proc. 2Jnt. Conf., on Fuzzy Logic and Neural Networks, Iizuka Japan, pp. 265-268