Multigranulation-based double-quantitative rough sets for multi-source event-based decision systems

Abstract

For the multi-source event-based decision system (MSEDS), each source exhibits its own one-sidedness and limitations. How to fuse the information contained in multiple sources to make a comprehensive decision has become an important research field. In this paper, the related concepts of support characteristic levels in one source are introduced from the viewpoint of single quantification and double quantification. The multigranulation-based single-quantitative rough set models, the related properties, and decision rules for single source based on the presented single-quantitative support characteristic levels are discussed. How to construct multigranulation-based single-quantitative and double-quantitative rough approximations in MSEDS and to analyze their corresponding properties and decision-making rules is addressed. To interpret the proposed multigranulation-based single-quantitative rough sets and double-quantitative rough sets in MSEDS, an illustrative example about an MSEDS formed by medical expert diagnosis is investigated, which is helpful to apply these developments to practical event-based decision-making problems.