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UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS

Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China

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JIYE LIANG

Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China

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YUHUA QIAN

Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China

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CHUANGYIN DANG

Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

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https://doi.org/10.1142/S0218488508005157Cited by:12 (Source: Crossref)

Abstract

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.

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