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Titlebook: Incomplete Information System and Rough Set Theory; Models and Attribute Xibei Yang,Jingyu Yang Book 2012 Science Press,Beijng and Springer

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31#
發(fā)表于 2025-3-26 23:28:22 | 只看該作者
32#
發(fā)表于 2025-3-27 01:34:32 | 只看該作者
Xibei Yang,Jingyu Yanglution and change using computational simulations enables to integrate social structures in the evolution of language, and how this can give rise to a new way to approach sociolinguistics. Finally, it explores applications for discourse analysis, semantics and cognition..978-3-030-04598-2
33#
發(fā)表于 2025-3-27 08:13:31 | 只看該作者
cations of basic complexical ideas need to be developed much farther in order to apply them to specific research. At the same time, the limits of complex adaptive systems as computational strategies must be accepted in the pursuit of a better understanding of the dynamic and evolutionary processes t
34#
發(fā)表于 2025-3-27 11:28:02 | 只看該作者
Xibei Yang,Jingyu Yanglution and change using computational simulations enables to integrate social structures in the evolution of language, and how this can give rise to a new way to approach sociolinguistics. Finally, it explores applications for discourse analysis, semantics and cognition..978-3-030-04598-2
35#
發(fā)表于 2025-3-27 16:03:31 | 只看該作者
36#
發(fā)表于 2025-3-27 18:22:02 | 只看該作者
Incomplete Information System and Rough Set TheoryModels and Attribute
37#
發(fā)表于 2025-3-27 23:54:27 | 只看該作者
38#
發(fā)表于 2025-3-28 03:41:10 | 只看該作者
Indiscernibility Relation, Rough Sets and Information Systemconditional probability of an equivalence class, which are classified into the target concept. Multigranulation rough set uses a family of the indiscernibility relation instead of a single one to construct rough approximation. In multigranulation rough set approach, the optimistic and pessimistic multigranulation rough sets are two basic models.
39#
發(fā)表于 2025-3-28 07:43:10 | 只看該作者
Expansions of Rough Sets in Incomplete Information Systemsbutes, the similarity relation, difference relation can be used to construct rough approximations, respectively. Finally, by considering the above two different semantic explanations of the unknown values, the characteristic relation can be used to construct rough approximation.
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