A semantic driven evolutive fuzzy clustering algorithm

IEEE International Conference on Fuzzy Systems

Volumn , Issue , 2007, Pages

  Fazendeiro, Paulo ^a,b   De Oliveira, José Valente ^c  

^a UNIVERSITY OF BEIRA INTERIOR   (Portugal)

^b IT The Portuguese Institute for Telecommunications

^c UNIVERSITY OF ALGARVE   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

CHLORINE COMPOUNDS; CLUSTER ANALYSIS; FLOW OF SOLIDS; FUZZY CLUSTERING; FUZZY LOGIC; FUZZY SETS; FUZZY SYSTEMS; INFORMATION THEORY; PARAMETER ESTIMATION; SEMANTICS;

DATA-DRIVEN DESIGN; EXPERIMENTAL STUDIES; FUZZY CLUSTERING ALGORITHMS; INTERNATIONAL CONFERENCES; LINGUISTIC INTERPRETATION; NUMBER OF CLUSTERS; SEMANTIC CONSTRAINTS; VARIABLE LENGTHS;

CLUSTERING ALGORITHMS;

EID: 50249157564     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2007.4295668     Document Type: Conference Paper

References (42)

1. J. Valente de Oliveira (1995) "A design methodology for fuzzy system interfaces", IEEE Trans. on Fuzzy Systems, 3(4):404-414.
2. W. Pedrycz, and J. Valente de Oliveira (1996) "An Algorithmic Framework for Development and Optimization of Fuzzy Models", Special issue of Fuzzy Sets and Systems on Fuzzy Modelling, 80(1):37-55.
3. J. Valente de Oliveira (1999) "Semantic Constraints for Membership Function Optimization", IEEE Trans. on Systems, Man, and Cybernetics, Part A: Systems and Man, 29(1): 128-138.
4. P. Fazendeiro and J. Valente de Oliveira (2002) "A Survey of Fuzzy Control Strategies for Neuromuscular Blockade Using Continuous Infusion of Atracurium", in Proc. FUZZ-IEEE'02, Honolulu, USA, 547-52.
5. P. Fazendeiro, and J. Valente de Oliveira (2005) "A Working Hypothesis on the Semantics/Accuracy Synergy", in Proc. Joint EUSFLAT-LFA 2005, Barcelona, Spain, pp. 266-271.
6. P. Fazendeiro, J. Valente de Oliveira and W. Pedrycz (2005) "Multiobjective evolutionary optimization of accuracy and interpretability for neuromuscular blockade control, in Proc. of IFSA 2005 - The International Fuzzy Systems Association World Congress, Beijing, China, pp. 908-913.
7. P. Fazendeiro, and J. Valente de Oliveira (2007) "A Multi-Objective Design of a Patient and Anaesthetist-Friendly Neuromuscular Blockade Controller", IEEE Trans. on BioMedical Engineering, to appear.
8. J. Casillas, O. Cordón, F. Herrera, and L. Magdalena (eds.) (2003) Accuracy Improvements in Linguistic Fuzzy Modeling, Physica-Verlag.
9. J. Casillas, O. Cordón, F. Herrera, and L. Magdalena (eds.) (2003) Interpretability Issues in Fuzzy Modeling, Physica-Verlag.
10. L. A. Zadeh (1965) "Fuzzy sets". Inform. Contr., 8:338-353.
11. E. H. Ruspini (1969) "A New Approach to Clustering", Information Control 15:22-32.
12. J. Dunn (1973) "A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters", Journal of Cybernetics, 3:32-57.
13. J. Bezdek (1981) Pattern Recognition with Fuzzy Objective Function Algoritms Plenum Press. New York.
14. A. Jain, M. Murty, and P. Flynn (1999) Data clustering: A review, ACM Comput. Surv., 31(3):264-323.
15. Rui Xu, Donald Wunsch II (2005) "Survey of Clustering Algorithms", IEEE Trans. on Neural Networks, 16(3):645-678
16. L. Hall, B. Ozyurt and J. Bezdek, (1999) "Clustering with a genetically optimized approach," IEEE Trans. on Evolutionary Computation, 3(2): 103-112.
17. Jianzhuang Liu and Weixin Xie (1995) "A genetics-based approach to fuzzy clustering," In Proc. of the 1995 IEEE International Conference on Fuzzy Systems,4:2233-2240.
18. Chih-Hsiu Wei and Chin-Shyung Fahn (1996) "A distributed approach to fuzzy clustering by genetic algorithms," Proceedings of the 1996 Asian Fuzzy Systems Symposium, IEEE, 350-357.
19. M. Egan (1998) "Locating clusters in noisy data: a genetic fuzzy cmeans clustering algorithm," Proceedings of the 1998 Conference of the North American Fuzzy Information Processing Society, IEEE, 178-182.
20. M.A. Egan, M. Krishnamoorthy, and K. Rajan (1998) "Comparative Study of a Genetic Fuzzy c-means Algorithm and a Validity Guided Fuzzy c-means Algorithm for Locating Clusters in Noisy Data," International Conference on Evolutionary Computation, pp. 440-445.
21. F. Klawonn and A. Keller (1998) "Fuzzy clustering with evolutionary algorithms," International Journal of Intelligent Systems, 13(1011):975-991.
22. M. Sarkar (1996) "Evolutionary programming-based fuzzy clustering," Proc. of the Fifth Annual Conference on Evolutionary Programming, MIT Press, 247-254.
23. Bo Yuan, G. Klir and J. Swan-Stone (1995) "Evolutionary fuzzy c-means clustering algorithm," Proc. of 1995 IEEE International Conference on Fuzzy Systems, 4:2221-2226.
24. T. Runkler (2005) "Ant colony optimization of clustering models," International Journal of Intelligent Systems, 20(12):1233-1261.
25. T. Runkler and C. Katz (2006) "Fuzzy Clustering by Particle Swarm Optimization," Proc. 2006 IEEE International Conference on Fuzzy Systems, pp. 601-608.
26. M. Halkidi, Y. Batistakis, and M. Vazirgiannis (2001) "Clustering algorithms and validity measures", Proc. 13th International Conference on Scientific and Statistical Database Management, pp.3-22.
27. G. Milligan and C. Cooper (1985) "An examination of procedures for Determining the Number of Clusters in a Data Set", Psychometrika, 50(2): 159-179.
28. C. Fralley and A. Raftery (1998) "How many Clusters? Which Clustering Method? Answers via Model-Based Cluster Analysis", The Computer Journal, 41(8):578-588.
29. U. Maulik and S. Bandyopadhyay (2002) "Performance evaluation of Some Clustering Algorithms and Validity Indices", IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(12):1650-1654.
30. N. Pal and J. Bezdek (1995) "On cluster validity for the fuzzy c-means model," IEEE Transactions on Fuzzy Systems, 3(3):370-379.
31. M. Halkidi, Y. Batistakis and M. Vazirgiannis (2001) "On Clustering Validation Techniques," Journal of Intelligent Information Systems, Kluwer Publishers, 17:2/3, 107-145.
32. H. Frigui and R. Krishnapuram (1997) "Clustering by competitive agglomeration," Pattern Recognition, 30(7):1109-1119.
33. H. Frigui and R. Krishnapuram (1999) "A robust competitive clustering algorithm with applications in computer vision," IEEE Trans. on Pattern Analysis and Machine Intelligence, 21(5):450-465.
34. A. Lorette, X. Descombes and J. Zerubia (2000) "Fully unsupervised fuzzy clustering with entropy criterion," Proceedings 15th International Conference on Pattern Recognition, (3):986-989.
35. U. Maulik and S. Bandyopadhyay (2003) "Fuzzy partitioning using a real-coded variable-length genetic algorithm for pixel classification," IEEE Trans. on Geoscience and Remote Sensing, 41(5):1075-1081.
36. X. Xie and G. Beni (1991) "A Validity Measure for Fuzzy Clustering", IEEE Trans. on Pattern Analysis and Machine Intelligence, 13:841-847.
37. F. Klawonn and F. Hoppner (2003) "What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier", Lecture Notes in Computer Science, Springer, 2810/2003:254-264.
38. R. Krishnapuram, J. Keller (1993) "A possibilistic approach to clustering", IEEE Trans. on Fuzzy Systems, 1:98-110.
39. R. Krishnapuram, J. Keller (1996) "The possibilistic C-Means algorithm: insights and recommendations", IEEE Trans. on Fuzzy Systems, 4:385-393.
40. L. Davis (1991) Handbook of genetic algorithms. Van Nostrand Reinold.
41. C. Coello, D. Van Veldhuizen, and G. Lamont (2002) Evolutionary Algorithms for Solving Multi-Objective Problems. Genetic Algorithms and Evolutionary Computation Series, Vol. 5, Springer.
42. T. A. Runkler and J. C. Bezdek (1999) "Alternating cluster estimation: A new tool for clustering and function approximation," IEEE Trans. Fuzzy Syst.,7:377-393.