Intuitionistic fuzzy hierarchical clustering algorithms

Journal of Systems Engineering and Electronics

Volumn 20, Issue 1, 2009, Pages 90-97

  Xu, Zeshui ^a,b  

^a SOUTHEAST UNIVERSITY   (China)

^b PLA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Distance measure; Hierarchical clustering; Interval valued intuitionistic fuzzy set; Intuitionistic fuzzy aggregation operator; Intuitionistic fuzzy set

Indexed keywords

DISTANCE MEASURE; HIER-ARCHICAL CLUSTERING; INTERVAL-VALUED INTUITIONISTIC FUZZY SET; INTUITIONISTIC FUZZY; INTUITIONISTIC FUZZY SETS;

BUILDING MATERIALS; CONSTRUCTION EQUIPMENT; FUZZY SETS; HAMMING DISTANCE; MATHEMATICAL OPERATORS;

CLUSTERING ALGORITHMS;

EID: 77957605917     PISSN: 10044132     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (41)

1. *-means-a generalized k-means clustering algorithm with unknown cluster number. Lecture Notes in Computer Science, 2002, 2412: 307-317.
2. Everitt B S, Landau S, Leese M. Cluster analysis. New York: Oxford University Press, 2001.
3. Pedrycz W. Knowledge-based clustering. Hoboken, New Jersey: John Wiley & Sons, Inc., 2005.
4. Atanassov K. Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 1986, 20: 87-96.
5. Atanassov K, Gargov G. Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 1989, 31: 343-349.
6. Zadeh L A. Fuzzy sets. Information and Control, 1965, 8: 338-353.
7. Atanassov K. Intuitionistic fuzzy sets: theory and applications. Heidelberg: Physica-Verlag, 1999.
8. Bustince H, Herrera F, Montero J. Fuzzy sets and their extensions: representation, aggregation and models. Heidelberg: Physica-Verlag, 2007.
9. Xu Z S. Intuitionistic fuzzy information: aggregation theory and applications. Beijing: Science Press, 2008.
10. Chen S M, Tan J M. Handling multicriteria fuzzy decisionmaking problems based on vague set theory. Fuzzy Sets and Systems, 1994, 67: 163-172.
11. Hong D H, Choi C H. Multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 2000, 114: 103-113.
12. Szmidt E, Kacprzyk J. Using intuitionistic fuzzy sets in group decision making. Control and Cybernetics, 2002, 31: 1037-1053.
13. Szmidt E, Kacprzyk J. A consensus-reaching process under intuitionistic fuzzy preference relations International Journal of Intelligent Systems, 2003, 18: 837-852.
14. Herrera F, Martínez L, Sánchez P J. Managing nonhomogeneous information in group decision making. European Journal of Operational Research, 2005, 166: 115-132.
15. Atanassov K, Pasi G, Yager R R. Intuitionistic fuzzy interpretations of multi-criteria multi-person and multimeasurement tool decision making. International Journal of Systems Science, 2005, 36: 859-868.
16. Xu Z S, Ronald R R. Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General Systems, 2006, 35: 417-433.
17. Xu Z S. A survey of preference relations. International Journal of General Systems, 2007, 36: 179-203.
18. Xu Z S. Intuitionistic preference relations and their application in group decision making. Information Sciences, 2007, 177: 2363-2379.
19. Liu H W, Wang G J. Multi-criteria decision-making methods based on intuitionistic fuzzy sets. European Journal of Operational Research, 2007, 179: 220-233.
20. Atanassov K, Georgiev C. Intuitionistic fuzzy prolog. Fuzzy Sets and Systems, 1993, 53: 121-128.
21. De S K, Biswas R, Roy A R. An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems, 2001, 117: 209-213.
22. Szmidt E, Kacprzyk J. A similarity measure for intuitionistic fuzzy sets and its application in supporting medical diagnostic reasoning. Lecture Notes in Artificial Intelligence, 2004, 3070: 388-393.
23. Xu Z S. On correlation measures of intuitionistic fuzzy sets. Lecture Notes in Computer Science, 2006, 4224: 16-24.
24. Li D F, Cheng C T. New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recognition Letters, 2002, 23: 221-225.
25. Hung W L, Yang M S. Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance. Pattern Recognition Letters, 2004, 25: 1603-1611.
26. Wang WQ, Xin X L. Distance measure between intuitionistic fuzzy sets. Pattern Recognition Letters, 2005, 26: 2063-2069.
27. Zhang C Y, Fu H Y. Similarity measures on three kinds of fuzzy sets. Pattern Recognition Letters, 2006, 27: 1307-1317.
28. Liang Z Z, Shi P F. Similarity measures on intuitionistic fuzzy sets. Pattern Recognition Letters, 2003, 24: 2687-2693.
29. Mitchell H B. On the Dengfeng-Chuntian similarity measure and its application to pattern recognition. Pattern Recognition Letters, 2003: 3101-3104.
30. Coker D. An introduction to intuitionistic fuzzy topological spaces. Fuzzy Set and Systems, 1997, 88: 81-89. (Pubitemid 127699076)
31. Samanta S K, Mondal T K. On intuitionistic gradation of openness. Fuzzy Set and Systems, 2002, 131: 323-336.
32. Abbas S E. On intuitionistic fuzzy compactness. Information Sciences, 2005, 173: 75-91.
33. Saadati R, Park J H. On the intuitionistic fuzzy topological spaces. Chaos, Solitons & Fractals, 2006, 27: 331-344.
34. Fayyad U M, Piatesky-Shapiro G, Smyth P, et al. Advances in knowledge discovery and data mining. Cambridge: AAAI Press, 1996.
35. Can F, Ozkarahan E. A dynamic cluster maintenance system for information retrieval. Proceedings of the Tenth Annual International ACM SIGIR Conference, 1987: 123-131.
36. Eissen M, Spellman P, Brown P, et al. Cluster analysis and display of genome- wide expression patterns. Proceeding of National Academy of Sciences of USA, 1998, 95: 14863-14868.
37. Zhang H M, Xu Z S, Chen Q. On clustering approach to intuitionistic fuzzy sets. Control and Decision, 2007, 22: 882-888.
38. Xu Z S. Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making. Fuzzy Optimization and Decision Making, 2007, 6: 109-121.
39. Xu Z S. Intuitionistic fuzzy aggregation operators. IEEE Trans. on Fuzzy Systems, 2007, 15: 1179-1187.
40. Anderberg M R. Cluster analysis for applications. New York: Academic Press, 1972.
41. Mingoti S A, Lima J O. Comparing SOM neural network with fuzzy c-means k-means and traditional hierarchical clustering algorithms. European Journal of Operational Research, 2006, 174: 1742-1759.