Abstract
This paper is devoted to some studies in reasoning decision rules of an uncertain information system which is an incomplete or imprecise even ill-defined database. At first, Theoretical aspects of the knowledge redundancy and the knowledge simplification of an uncertain system is discussed based on theoretical aspects of rough sets. A maximal information coverage rate is defined with the acquired data of a decision table in an information system on condition attributes. A criterion of the knowledge simplification and a basic algorithm realization of reasoning decision rules of an uncertain information system is presented to induce a mathematical model of an uncertain system with the maximum information coverage. The feasibility of the proposed approach of reasoning decision rules is validated by some of examples here.
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Zeng, H., Zeng, X. (2009). Reasoning Decision Rules of an Uncertain System. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds) Rough Sets and Knowledge Technology. RSKT 2009. Lecture Notes in Computer Science(), vol 5589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02962-2_80
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DOI: https://doi.org/10.1007/978-3-642-02962-2_80
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