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| Optimal Granularity Selections in Consistent Incomplete Multi-granular Labeled Decision Systems |
| WU Weizhi, CHEN Ying, XU Youhong, GU Shenming |
Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province,
Zhejiang Ocean University, Zhoushan 316022
School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan 316022 |
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Abstract Aiming at knowledge acquisition in incomplete information systems with multi-granular labels, the concept of incomplete multi-granular labeled information systems is firstly introduced.Similarity relations of an incomplete multi-granular labeled information system are then defined.Representations of information granules with different levels of granulation as well as their relationships are also explored.Lower and upper approximations based on similarity relations with different levels of granulation are further defined and their properties are presented.Finally, by belief and plausibility functions in Dempster-Shafer theory of evidence, optimal granularity selections in consistent incomplete multi-granular labeled decision systems are discussed.
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Received: 29 May 2015
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2016, Vol. 29 
