The Application of Fuzzy Equivalence Relation Based on the Quotient Space in Cluster Analysis

Article Preview

Abstract:

A fuzzy clustering analysis model based on the quotient space is proposed. Firstly, the conversion from coarse to fine granularity and the hierarchical structure are used to reduce the multidimensional samples. Secondly, the fuzzy compatibility relation matrix of the model is converted into fuzzy equivalence relation matrix. Finally, the diagram of clustering genealogy is generated according to the fuzzy equivalence relation matrix, which enables the dynamic selection of different thresholds to effectively solve the problem of cluster analysis of the samples with multi-dimensional attributes.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

333-339

Citation:

Online since:

October 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Zhang Ling, Zhang Bo. The problem solving theory and application [M]. Beijing: Tsinghua University press, (1990).

Google Scholar

[2] Zhang Ling, Zhang Bo. Fuzzy quotient space theory [J]. Journal of software, 2003, 14 (4): 770-776.

Google Scholar

[3] D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets[J], International Journalof General System, 1990, 17: 91-109.

DOI: 10.1080/03081079008935107

Google Scholar

[4] Zhang Ling. Discussion on Granular Computing [J]. Computer and information technology, 2003, 119 (8).

Google Scholar

[5] Zhang Ling, Zhang Bo. The theory and applications of problem solving- Application and theory of quotient space granularity (Second Edition), Beijing: Tsinghua University press, (2007).

Google Scholar

[6] Zhang Qinghua, Wang Guoyin. Hierarchical structure analysis of fuzzy quotient space [J]. pattern recognition and artificial intelligence. 2008, 21(5): 627-634.

Google Scholar

[7] Zhang Yanping. The quotient space and granular computing theory and method of structured problem solving [M]. Beijing: Science Press, (2010).

Google Scholar

[8] Zhang Yanping, Zhang Ling, Wu Tao. Description of the different granularity world- Quotient space theory [J]. Chinese Journal of computers, 2004, 27(3): 328-333.

Google Scholar

[9] Lu Bin. Research on the method of fuzzy clustering based on quotient space[J]. microcomputer information, 2010, 26(1): 8-10.

Google Scholar

[10] Zhi Xiaobin, fan Jiulun. Fuzzy maximum scatter difference discriminant adaptive feature extraction algorithm based on Fuzzy Clustering [J], computer application, 2011, 39(6): 1358-1363. 11 Lou Xiaojun Li Junying Liu.

DOI: 10.3724/sp.j.1001.2009.03410

Google Scholar