首页> 外文期刊>International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems >UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS
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UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS

机译:基于知识粒度的不完备信息系统粗糙集不确定性度量

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摘要

Rough set theory is a relatively new mathematical tool for computer applications in circumstances characterized by vagueness and uncertainty. In this paper, we address uncertainty of rough sets for incomplete information systems. An axiom definition of knowledge granulation for incomplete information systems is obtained, under which a measure of uncertainty of a rough set is proposed. This measure has some nice properties such as equivalence, maximum and minimum. Furthermore, we prove that the uncertainty measure is effective and suitable for measuring roughness and accuracy of rough sets for incomplete information systems.
机译:粗糙集理论是在模糊和不确定性特征下用于计算机应用的相对较新的数学工具。在本文中,我们解决了不完整信息系统的粗糙集的不确定性。获得了不完备信息系统知识粒度的公理定义,提出了一种粗糙集的不确定性度量。此度量具有一些不错的属性,例如等效性,最大值和最小值。此外,我们证明了不确定性度量是有效的并且适合于测量不完整信息系统的粗糙集的粗糙度和准确性。

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