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Attribute reduction in ordered information systems based on evidence theory

机译:基于证据理论的有序信息系统属性约简

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Attribute reduction is one of the most important problems in rough set theory. However, in real-world lots of information systems are based on dominance relation in stead of the classical equivalence relation because of various factors. The ordering properties of attributes play a crucial role in those systems. To acquire brief decision rules from the systems, attribute reductions are needed. This paper deals with attribute reduction in ordered information systems based on evidence theory. The concepts of plausibility and belief consistent sets as well as plausibility and belief reducts in ordered information systems are introduced. It is proved that a plausibility consistent set must be a consistent set and an attribute set is a belief reduct if and only if it is a classical reduction in ordered information system.
机译:属性约简是粗糙集理论中最重要的问题之一。然而,由于各种因素,在现实世界中,许多信息系统基于优势关系而不是经典的等价关系。属性的排序属性在这些系统中起着至关重要的作用。为了从系统获取简短的决策规则,需要减少属性。本文研究了基于证据理论的有序信息系统的属性约简。介绍了有序和信念一致集的概念,以及有序信息系统中的似然和信念减少。事实证明,当且仅当它是有序信息系统的经典约简时,似然一致集必须是一致集,而属性集是置信度。

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