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- Title
Uncertainty Measures for Multigranulation Approximation Space.
- Authors
Lin, Guoping; Liang, Jiye; Qian, Yuhua
- Abstract
Multigranulation rough set theory is a relatively new mathematical tool for solving complex problems in the multigranulation or distributed circumstances which are characterized by vagueness and uncertainty. In this paper, we first introduce the multigranulation approximation space. According to the idea of fusing uncertain, imprecise information, we then present three uncertainty measures: fusing information entropy, fusing rough entropy, and fusing knowledge granulation in the multigranulation approximation space. Furthermore, several essential properties (equivalence, maximum, minimum) are examined and the relationship between the fusion information entropy and the fusion rough entropy is also established. Finally, we prove these three measures are monotonously increasing as the partitions become finer. These results will be helpful for understanding the essence of uncertainty measures in multigranulation rough space and enriching multigranulation rough set theory.
- Subjects
TOPOLOGICAL spaces; UNCERTAINTY (Information theory); APPROXIMATION theory; PROBLEM solving; ENTROPY (Information theory); ROUGH sets
- Publication
International Journal of Uncertainty, Fuzziness & Knowledge-Based Systems, 2015, Vol 23, Issue 3, p443
- ISSN
0218-4885
- Publication type
Article
- DOI
10.1142/s0218488515500191