Regression methods for hesitant fuzzy preference relations
In this paper, we develop two regression methods that transform hesitant fuzzy preference relations (HFPRs) into fuzzy preference relations (FPRs). On the basis of the complete consistency, reduced FPRs with the highest consistency levels can be derived from HFPRs. Compared with a straightforward me...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2014-01-01
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| Series: | Technological and Economic Development of Economy |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/TEDE/article/view/4328 |
| Summary: | In this paper, we develop two regression methods that transform hesitant fuzzy preference relations (HFPRs) into fuzzy preference relations (FPRs). On the basis of the complete consistency, reduced FPRs with the highest consistency levels can be derived from HFPRs. Compared with a straightforward method, this regression method is more efficient in the Matlab environment. Based on the weak consistency, another regression method is developed to transform HFPRs into reduced FPRs which satisfy the weak consistency. Two algorithms are proposed for the two regression methods, and some examples are provided to verify the practicality and superiority of the proposed methods. |
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| ISSN: | 2029-4913 2029-4921 |