首页|Multiview sequential three-way decisions based on partition order product space
Multiview sequential three-way decisions based on partition order product space
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NSTL
Elsevier
In granular computing, a set of attributes (features) is often selected as a view to describe objects from a particular angle. In each view, objects can be further described from different levels of granularities (abstraction), and each granularity determines a level. Multiview and multilevel are two basic principles of granular computing, which render a solution more comprehensive and reasonable. From the viewpoint of granular computing, existing three-way decisions cannot effectively combine multiview and multilevel to make decisions. As a new granular computing model, the partition order product space solves a problem from multiple views and at multiple levels in each view, which follows the principles of multiview and multilevel. In this paper, we discuss three-way decisions based on partition order product space. First, we propose two search algorithms: depth-first and breadth first searching algorithms, to obtain a solution for problem solving in partition order product space. Second, we introduce two fusion strategies to fuse multiple one-level views: optimistic fusion method and pessimistic fusion method. Consequently, based on two search algorithms and two fusion strategies, we propose four multiview sequential three-way decisions, which can simultaneously make decisions from multiple views and multiple levels. Experimental results demonstrate the effectiveness of the proposed models. (c) 2022 Elsevier Inc. All rights reserved.
Three-way decisionsGranular computingPartition order product spaceMultiviewMultilevelRECOGNITIONSIMILARITY
NSTL
Elsevier
