2024-03-29T07:57:52Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1342472016-10-20T09:33:59Zcom_10261_60com_10261_4col_10261_313
00925njm 22002777a 4500
dc
Torra, Vicenç
author
Stokes, Klara
author
Narukawa, Yasuo
author
2012
Fuzzy measures are monotonic set functions on a reference set; they generalize probabilities replacing the additivity condition by monotonicity. The typical application of these measures is with fuzzy integrals. Fuzzy integrals integrate a function with respect to a fuzzy measure, and they can be used to aggregate information from a set of sources (opinions from experts or criteria in a multicriteria decision-making problem). In this context, background knowledge on the sources is represented by means of the fuzzy measures. For example, interactions between criteria are represented by means of nonadditive measures. In this paper, we introduce fuzzy measures on multisets. We propose a general definition, and we then introduce a family of fuzzy measures for multisets which we show to be equivalent to distorted probabilities when the multisets are restricted to proper sets. © 2012 IEEE.
IEEE Transactions on Fuzzy Systems 20 (6): 1032- 1045 (2012)
http://hdl.handle.net/10261/134247
10.1109/TFUZZ.2012.2191413
Fuzzy measures
Multisets
Aggregation operators
An extension of fuzzy measures to multisets and its relation to distorted probabilities