A new heuristic algorithm of fuzzy clustering

• Autorzy: Viattchenin D. A.
• Języki publikacji: EN

Abstrakty

EN

This paper deals with a new method of fuzzy clustering. The basic concepts of the method are introduced as resulting from the consideration of the fundamental fuzzy clustering problem. The paper provides the description of the general plan of the algorithm and an illustrative example. An analysis of the experimental results of the method's application to the Anderson's Iris data is carried out. Some preliminary conclusions and the ways of prospective investigations are given.

Słowa kluczowe

EN

fuzzy clustering; fuzzy tolerance; fuzzy cluster; membership degree; allotment; typical point

PL

grupowanie rozmyte; przydział; punkt typowy

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2004
• Tom: Vol. 33, no 2
• Strony: 323--340
• Opis fizyczny: Bibliogr. 22 poz.

Twórcy

autor

Viattchenin D. A.

• National Academy of Sciences of Belarus GIS Research and Engineering Centre Surganov St. 6, 220012 Minsk, Belarus

Bibliografia

• Anderson, E. (1934) The irises of the Gaspe peninsula. Bulletin of the American Iris Society 59, 2–5.
• Bellman, R., Kalaba, R. and Zadeh, L.A. (1966) Abstraction and pattern classification. Journal of Mathematical Analysis and Applications13, 1–7.
• Bezdek, J.C. (1981) Pattern Recognition with Fuzzy Objective Function Algorithms. New York, Plenum Press.
• Couturier, A. and Fioleau, B. (1997) Recognizing stable corporate groups:a fuzzy classification method. Fuzzy Economic ReviewII, 35–45.
• Dunn, J.C. (1974) A fuzzy relative of the ISODATA process and its use indetecting compact, well-separated clusters. Journal of Cybernetics 3, 32–57.
• Gitman, I. and Levine, M.D. (1970) An algorithm for detecting unimodal fuzzy sets and its application as a clustering technique. IEEE Transactionson Computers C-19, 583–593.
• Ḧoppner, F., Klawonn, F. and Kruse, R. (1997) Fuzzy-clusteranalyse verfahren f ̈ur die bilderkennung, classification und datenanalyse. Wiesbaden, Vieweg Verlag.
• Jajuga, K. (1993) L1-norm based fuzzy clustering. Fuzzy Sets and Systems 39, 43–50.
• Pedrycz, W. (1985) Algorithms of fuzzy clustering with partial supervision. Pattern Recognition Letters 3, 13–20.
• Radecki, T. (1977) Level fuzzy sets. Journal of Cybernetics 7, 189–198.
• Roubens, M. (1978) Pattern classification problems and fuzzy sets. Fuzzy Sets and Systems1, 239–253.
• Ruspini, E.H. (1970) Numerical methods for fuzzy clustering. Information Sciences 2, 319–350.
• Ruspini, E.H. (1982) Recent Developments in Fuzzy Clustering. In: R.R.Yager, ed., Fuzzy Set and Possibility Theory: Recent Developments. New York, Pergamon Press.
• Tamura, S., Higuchi, S. and Tanaka, K. (1971) Pattern Classification Basedon Fuzzy Relations. IEEE Transactions on Systems, Man, and Cybernetics SMC-1, 61-66.
• Viattchenin, D.A. (1997 ) Some remarks to concept of fuzzy similarity relation for fuzzy cluster analysis. In:Proceedings of the Fourth International Conference PRIP’971. Szczecin, Wydawnictwo Uczelniane Politechniki Szczecinskiej.
• Viattchenin, D.A. (1998) On projections of fuzzy similarity relations. In:Proceedings of the Fifth International Conference CDAM’98 2. Minsk, Belarusian State University.
• Viattchenin, D.A. (1999) Remarks on kinds of fuzzy clusters. In: Proceedings of the International Conference ”Quality of Life: Statistical Data Analysis”. Wroclaw, Wroclaw University of Economics.
• Viattchenin, D.A. (2001) On the intersection of fuzzy clusters. In:Proceedings of International Scientific and Practical Workshop ”Integrated Models and Soft Computing in Artificial Intelligence”. Moscow, Science (in Russian).
• Viattchenin, D.A. (2002) Human-computer approach to fuzzy classification problem based on the concept of representation. In: Proceedings of the Second International Conference ”Quality of Life”. Wroclaw, Wroclaw University of Economics.
• Windham, M.R. (1985) Numerical classification of proximity data with assignment measures. Journal of Classification 2, 157–172.
• Zadeh, L.A. (1965) Fuzzy Sets. Information and Control8, 338–353.
• Zadeh, L.A. (1977) Fuzzy Sets and Their Application to Pattern Classification and Cluster Analysis. In: J.Van Ryzin, ed., Classification and Clustering. New York, Academic Press.