Distance and similarity measures of dual hesitant fuzzy sets with their applications to multiple attribute decision making
The Dual Hesitant Fuzzy Sets (DHFSs) is a useful tool to deal with vagueness and ambiguity in the multiple attribute decision making (MADM) problems. The distance and similarity measures analysis are important research topics. In this paper, we propose a variety of distance measures for dual hesitan...
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| Vydáno v: | 2014 IEEE International Conference on Progress in Informatics and Computing s. 88 - 92 |
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| Hlavní autoři: | , , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.05.2014
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| Témata: | |
| ISBN: | 9781479920334, 1479920339 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The Dual Hesitant Fuzzy Sets (DHFSs) is a useful tool to deal with vagueness and ambiguity in the multiple attribute decision making (MADM) problems. The distance and similarity measures analysis are important research topics. In this paper, we propose a variety of distance measures for dual hesitant fuzzy sets, based on which the corresponding similarity measures can be obtained. We investigate the connections of the aforementioned distance measures and further develop a number of dual hesitant ordered weighted distance measures. Finally, we present a TOPSIS approach based on proposed distance measures for the weapon selection problem. |
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| ISBN: | 9781479920334 1479920339 |
| DOI: | 10.1109/PIC.2014.6972302 |

