Name
Abstract | ||
|---|---|---|
Motivated by a specific decision-making situation, this work proposes the concept and definition of unsymmetrical basic uncertain information which is a further generalization of basic uncertain information and can model uncertainties in some new decision-making situations. We show that unsymmetrical basic uncertain information in some sense can model linguistic hedges such as "at least" and "at most". Formative weighted arithmetic means and induced aggregations are defined for the proposed concept. Rules-based decision making and semi-copula based integral for this concept with some numerical examples are also presented.U |
Year | DOI | Venue |
|---|---|---|
2022 | 10.3233/JIFS-220593 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | DocType | Volume |
Aggregation operators, basic uncertain information, evaluation, information fusion, integral, uncertainty, unsymmetrical basic uncertain information | Journal | 43 |
Issue | ISSN | Citations |
4 | 1064-1246 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| LeSheng Jin | 1 | 1 | 1.03 |
| Ronald R. Yager | 2 | 9852 | 1562.99 |
| Zhen-Song Chen | 3 | 2 | 2.73 |
| Mesiar Mesiar | 4 | 0 | 0.34 |
| Humberto Bustince | 5 | 1938 | 134.10 |