Variable Precision Based Optimal Scale Combinations in Generalized Multi-scale Decision Systems
NIU Dongran1,2, WU Weizhi1,2, LI Tongjun1,2
1.School of Mathematics, Physics and Information Science, Zhe-jiang Ocean University, Zhoushan 316022; 2.Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022
Abstract:To solve the problems of knowledge representation and knowledge acquisition in generalized multi-scale decision systems, optimal scale combination selections based on dual probabilistic rough set model in generalized multi-scale decision systems are discussed. Notions of β lower approximation optimal scale combination, β upper approximation optimal scale combination, β belief distribution optimal scale combination and β plausibility distribution optimal scale combination in generalized multi-scale decision systems are defined and their properties are examined. Finally, relationships among different notions of optimal scale combinations in generalized multi-scale decision systems are analyzed. It is proved that for some special thresholds, β lower approximation optimal scale combination is equivalent to the maximum distribution optimal scale combination, whereas β upper approximation optimal scale combination is equivalent to the generalized decision optimal scale combination.
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