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An MST cluster analysis method under hesitant fuzzy environment

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Hesitant fuzzy sets (HFSs) are useful means to describe and deal with uncertain data. In this article, a minimal spinning tree (MST) algorithm based clustering technique under hesitant fuzzy environment is proposed. We first introduce the concepts of graph, MST, HFS, and hesitant fuzzy distance. Then, we present a hesitant fuzzy MST clustering algorithm to perform clustering analysis of HFSs via some hesitant fuzzy distances, and finally illustrate the effectiveness of our algorithm through two numerical examples.
Rocznik
Strony
645--666
Opis fizyczny
Bibliogr. 30 poz., il.
Twórcy
autor
autor
  • School of Economics and Management, Southeast University Nanjing, Jiangsu 211189, China
Bibliografia
  • Anderberg, M. (1973) Cluster Analysis for Applications. Academic Press. New York, NY.
  • Atanassov, K. (1986) Intuitionistic fuzzy sets. Fuzzy Sets and Systems 20 (1), 87-96.
  • Chen, D. S., Li, K. X. and Zhao, L. B. (2007) Fuzzy graph maximal tree clustering method and its application. Operations Research and Management Science, 16 (3), 69-73.
  • Dong, Y. H., Zhuang, Y. T., Chen, K. and Tai, X. Y. (2006) A hierarchical clustering algorithm based on fuzzy graph connectedness. Fuzzy Sets and Systems, 157 (11), 1760-1774.
  • Dubois, D. and Prade, H. (1980) Fuzzy Sets and Systems: Theory and Applications. Academic Press. New York.
  • Everitt, B., Landau, S. and Leese, M. (2001) Cluster Analysis, 4th edition. Arnold, London.
  • Gaertler, M. (2002) Clustering with spectral methods. Master’s thesis, Universität Konstanz.
  • Harary, F. (1969) Graph Theory. Reading, Addison-Wesley.
  • Hartigan, J. (1975) Clustering Algorithms. John Wiley & Sons, New York, NY.
  • Jain, A. and Dubes, R. (1988) Algorithms for Clustering Data. Prentice Hall, Englewood Cliffs, NJ.
  • Kruskal, J. B. (1965) On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7, 48-50.
  • Miyamoto, S. (2000) Multisets and fuzzy multisets. In: Z. Q. Liu and S. Miyamoto, eds., Soft Computing and Human-Centered Machines. Springer, Berlin, 9-33.
  • Miyamoto, S. (2005) Remarks on basics of fuzzy sets and fuzzy multisets. Fuzzy Sets and Systems, 156 (3), 427-431.
  • Prim, R. C. (1957) Shortest connection networks and some generalizations. Bell System Technology Journal, 36, 1389-1401.
  • Ruspini, E. H. (1969) A new approach to clustering. Information and Control, 15 (1), 22-32.
  • Schaeffer, S. E. (2007) Graph clustering. Computer Science Review, 1 (1), 27-64.
  • Torra, V. (2010) Hesitant Fuzzy Sets. International Journal of Intelligent Systems, 25 (6), 529-539.
  • Torra, V., Narukawa, Y. (2009) On hesitant fuzzy sets and decision. The 18th IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 1378-1382.
  • Torra, V. and Miyamoto, S. (2011) A definition for I-fuzzy partition. Soft Computing, 15, 363-369.
  • Torra, V. and Min, J.-H. (2010a) Applying I-Fuzzy Partitions to Represent Sets of Fuzzy Partitions. The 13th International Conference on Artificial Intelligence Research and Development, Tarragona, Spain, 201-206.
  • Torra, V. and Min, J.-H. (2010b) I-Fuzzy Partitions for Representing Clustering Uncertainties. The 10th International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland, Springer, 240-247.
  • Xia, M. M. and Xu, Z. S. (2011) Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning 52 (3), 395-407.
  • Xia, M. M., Xu, Z. S. and Chen, N. (2011) Induced aggregation under confidence levels. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 19 (2), 201-227.
  • Xu, Z. S. and Xia, M. M. (2011a) Distance and similarity measures for hesitant fuzzy sets. Information Sciences, 181 (11), 2128-2138.
  • Xu, Z. S. and Xia, M. M. (2011b) On distance and correlation measures of hesitant fuzzy information. International Journal of Intelligent Systems, 26 (5), 410-425.
  • Yager, R. R. (1986) On the theory of bags. International Journal of General Systems, 13 (1), 23-37.
  • Zadeh, L. A. (1965) Fuzzy sets. Information and Control 8 (3) 338-353.
  • Zahn, C. T. (1971) Graph-theoretical methods for detecting and describing gestalt clusters. IEEE Transactions on Computers, 20 (1), 68-86.
  • Zhang, S., Shen, M. X. and Wang, Y. L. (2009) Intuitionistic fuzzy group decision making method based on evidence combination methods. Military Operations Research and Systems Engineering 21, 39-42.
  • Zhao, H, Xu, Z. S., Liu, S. S. and Wang, Z. (2012) Intuitionistic fuzzy MST clustering algorithms. Computers & Industrial Engineering, 62 (4), 1130-1140.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATC-0011-0121
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