Abstract
Entropy theory is a useful measure of uncertainty about the information systems. In this paper, we address uncertainty roughness measures of knowledge and rough sets by introducing rough entropy, and some of its important properties are given, then we prove the rough entropy is more accurate than the rough degree to measure the roughness of rough sets in interval ordered information systems and through some examples are illustrated.These results will be very helpful for understanding the essence of knowledge content and uncertainty measurement in future research works of interval ordered information.
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Wang, J. (2011). Uncertainty Measures of Roughness Based on Interval Ordered Information Systems. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_17
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DOI: https://doi.org/10.1007/978-3-642-24728-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24727-9
Online ISBN: 978-3-642-24728-6
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