Latest revision as of 10:44, 15 February 2021

Abstract

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.

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• http://dx.doi.org/10.3390/info10020071 under the license https://creativecommons.org/licenses/by

• http://dx.doi.org/10.3390/info10020071 under the license http://creativecommons.org/licenses/by/3.0/

• https://www.mdpi.com/2078-2489/10/2/71/pdf under the license https://creativecommons.org/licenses/by/4.0

• http://www.mdpi.com/2078-2489/10/2/71/pdf,

http://dx.doi.org/10.3390/info10020071 under the license cc-by

• https://dblp.uni-trier.de/db/journals/information/information10.html#WuZSWT19,

https://www.mdpi.com/2078-2489/10/2/71/htm,

https://www.mdpi.com/2078-2489/10/2/71/pdf,

https://doi.org/10.3390/info10020071,

https://academic.microsoft.com/#/detail/2916199365 under the license https://creativecommons.org/licenses/by/4.0/

• https://www.mdpi.com/2078-2489/10/2/71,

https://doaj.org/toc/2078-2489