Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Li, Hongxu | Yang, Yang*; | Yin, Songyi
Affiliations: School of Management Engineering and Business, Hebei University of Engineering, Handan, China
Correspondence: [*] Corresponding author. Yang Yang, School of Management Engineering and Business, Hebei University of Engineering, Handan, China. E-mail: [email protected].
Abstract: The q-rung orthopair fuzzy set is a significant part of the existing orthopair fuzzy sets, whose advantage is to more comprehensively describe uncertain information. For q-rung orthopair fuzzy sets, the correlation between them is generally measured by the correlation coefficient. In order to express the positive and negative correlations of q-rung orthopair fuzzy sets simultaneously from a statistical perspective, and to reflect the attitude of decision makers, in this paper, two new correlation coefficients of q-rung orthopair fuzzy sets are proposed and investigated. Firstly, a λ-variance-based correlation coefficient of q-rung orthopair fuzzy sets is proposed from the statistical viewpoint. Secondly, a λ-matching-function-based correlation coefficient of q-rung orthopair fuzzy sets is defined from the perspective of vector calculation. In the end, an example of clustering analysis is presented to verify the feasibility and superiority of the proposed correlation coefficients by comparing with other existing correlation coefficient of q-rung orthopair fuzzy sets. It can be seen from the clustering results that the two new λ-correlation coefficients not only consider the positive or negative correlation at the same time, but also can be dynamically adjusted according to the needs of decision makers. Furthermore, clustering results using λ-variance-based and λ-matching-function-based correlation coefficients converge faster than clustering results using the existing correlation coefficient in the q-rung orthopair fuzzy environment.
Keywords: q-rung orthopair fuzzy set, correlation coefficient, clustering analysis
DOI: 10.3233/JIFS-191553
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 581-591, 2020
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]