Local Optimal Scale Combination Selections in Inconsistent Generalized Multi-scale Decision Systems
WU Weizhi1,2, SUN Yu1,2, WANG Xia1,2, ZHENG Jiawen1,2
1. School of Information Engineering, Zhejiang Ocean University, Zhoushan 316022 2. Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022
Abstract To investigate knowledge acquisition for objects in inconsistent generalized multi-scale decision systems, the concept of local optimal scale combination is presented. Firstly, the notion of scale combination in a generalized multi-scale information system is introduced. Information granules with different scale combinations as well as their relationships from generalized multi-scale information systems are formulated. Lower and upper approximations of sets with different scale combinations in generalized multi-scale information systems are further constructed and their properties are examined. Finally, concepts of seven types of local optimal scale combinations for an object in an inconsistent generalized multi-scale decision system are defined and their relationships are clarified. It is proved that there are five different types of local optimal scale combinations in fact.
Fund:National Natural Science Foundation of China(No.61976194,41631179,62076221)
Corresponding Authors:
WU Weizhi, Ph.D., professor. His research interests include rough set, granular computing,data mining and artificial intelligence.
About author:: SUN Yu, master student. Her research interests include rough set and granular computing.WANG Xia, Ph.D., associate professor. Her research interests include concept lattice, rough set and granular computing.ZHENG Jiawen, master student. Her research interests include rough set and granular computing.
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2021, Vol. 34 
