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Abstrakty
The paper compares two different approaches in the application of modular fuzzy systems. The first approach is standard one – each fuzzy submodel works in 3 steps: fuzzification, inference and defuzzification. In the second approach, there are omitted some unnecessary fuzzification and defuzzification operations in submodels. Performed experiments enabled the comparison of an accuracy and an implementation simplicity of described methods.
Czasopismo
Rocznik
Tom
Strony
179--187
Opis fizyczny
Bibliogr. 10 poz., rys., tab.
Twórcy
autor
- West Pomeranian University of Technology, Szczecin, Faculty of Computer Science and Information Technology
Bibliografia
- [1] Addabbo T., Facchinetti G., Mastroleo G., Solinas G. A fuzzy way to “measure” quality of work in a multidimensional perspective. Proceedings of the 13th International Multi-Conference on Advanced Computer Systems, vol. 1, Międzyzdroje, Poland, pp. 13-24, 2006
- [2] Awadalla, M. Hierarchical and modular fuzzy architecture for multiple mobile robots. International Journal of Computer Aided Engineering and Technology, vol. 1, no 2, pp.127-144, 2009
- [3] Caponetto R., Fortuna L., Nunnari G., Occhipinti L. Xibilia M. Soft computing for greenhouse climate control. IEEE Transaction on Fuzzy Systems, vol. 8, no 6, pp. 753-760, 2000
- [4] Delgado M., Zuben F.V. Gomide F. Modular and hierarchical evolutionary design of fuzzy systems. Proceedings of the Genetic and Evolutionary Computation Conference – GECCO'99, vol. 1, Orlando, USA, pp. 180-187,1999
- [5] Facchinetti G., Marchi G., Mastroleo G. Vignola M. Fuzzy model for international market selection – a real italian case. Polish Journal of Environmental Studies, vol. 17, no 4C, pp. 35-41, 2008
- [6] Łęski J. Neuro-fuzzy systems. Wydawnictwa Naukowo-Techniczne, Warszawa, 2008, [in Polish]
- [7] Maeda S., Watanabe T., Fujioka, R. Collaborative filtering based on modular fuzzy model concept. Proceedings of the 24th Fuzzy System Symposium, Osaka, 2008
- [8] Piegat A. Fuzzy modeling and control. Physica Verlag, Heidelberg-New York, 2001
- [9] Rejer I. Rule reduction in a fuzzy model of a chain system. Proceedings of the 13th International Multi-Conference on Advanced Computer Systems, vol. 1, Międzyzdroje, Poland, pp. 193-202, 2006
- [10] Sriraman A., Mayorga, R. A fuzzy inference system approach for greenhouse climate control. Environmental Informatics Archives, vol. 2, pp. 699-710, 2004
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS3-0014-0064