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| Scale Combinations in Inconsistent Generalized Multi-scale Decision Systems |
| WU Weizhi1,2, ZHUANG Yubin1,2, TAN Anhui1,2, XU Youhong1,2 |
1.School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan 316022
2.Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022 |
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Abstract To investigate knowledge acquisition in the sense of decision rules in inconsistent generalized multi-scale decision systems, the concept of scale combinations in generalized multi-scale information systems is firstly introduced.Information granules with different scale combinations as well as their relationships from generalized multi-scale information systems are then represented.Lower and upper approximations of sets with different scale combinations are further defined and their properties are explored.Finally, optimal scale combinations in inconsistent generalized multi-scale decision systems are discussed.Belief and plausibility functions in the Dempster-Shafer theory of evidence are employed to characterize optimal scale combinations in inconsistent generalized multi-scale decision systems.
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Received: 12 April 2018
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| Fund:Supported by National Natural Science Foundation of China(No.61573321,41631179,61602415), Natural Science Foundation of Zhejiang Province(No.LY18F030017) |
| About author:: (WU Weizhi(Corresponding author), Ph.D., professor. His research interests include rough sets, granular computing, data mining and artificial intelligence.)(ZHUANG Yubin, master student. His research interests include rough sets and data mining.)(TAN Anhui, Ph.D., lecturer. His research interests include rough sets, granular computing, data mining and artificial intelligence.)(XU Youhong, master, associate professor. Her research interests include rough sets, granular computing and artificial intelligence.) |
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2018, Vol. 31 
