Based on comparative studies on correlation coefficient theory and utility theory, a series of rules that utility functions on dual hesitant fuzzy rough sets (DHFRSs) should satisfy, and a kind of novel utility function on DHFRSs are proposed. The characteristic of the introduced utility function is a parameter, which is determined by decision-makers according to their experiences. By using the proposed utility function on DHFRSs, a novel dual hesitant fuzzy rough pattern recognition method is also proposed. Furthermore, this study also points out that the classical dual tool is suitable to cope with dynamic data in exploratory data analysis situations, while the newly proposed one is suitable to cope with static data in confirmatory data analysis situations. Finally, a medical diagnosis and a traffic engineering example are introduced to reveal the effectiveness of the newly proposed utility functions on DHFRSs.

Document type: Article

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.3390/info10020071 under the license cc-by
https://academic.microsoft.com/#/detail/2916199365 under the license https://creativecommons.org/licenses/by/4.0/
Back to Top

Document information

Published on 01/01/2019

Volume 2019, 2019
DOI: 10.3390/info10020071
Licence: Other

Document Score


Views 0
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?