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Home > Archive>Volume 27, Issue 7, 2016 >1645-1654. DOI:10.13328/j.cnki.jos.005036
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Statistical Rough Sets
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National Basic Research Program of China (973) (2012CB316205); National High Technology Research and Development Program of China (863) (2014AA015204); National Natural Science Foundation of China (61532021, 61202114, 61272137); Research Funds of Renmin University of China (15XNLQ06)

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    Abstract:

    This paper introduces random sampling into traditional fuzzy rough methods and proposes a random sampling based statistical rough set model. The work focuses on how to bring random sampling into traditional rough set. First, random sampling is used to propose a concept of k-limit, which can dramatically reduce the amount of computation during the computing of lower approximation value. Then, statistical upper and lower approximation is formulated. By mathematical reasoning, sufficient theorem and proof are used to valid the reliability of new model. Finally, numerical experiments illustrate the efficiency of the proposed statistical rough sets.

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陈俞,赵素云,陈红,李翠平,孙辉.统计粗糙集.软件学报,2016,27(7):1645-1654

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History
  • Received:September 26,2015
  • Revised:January 12,2016
  • Online: March 24,2016
Links:Institute of Software, CASChina Computer FederationCASNSFC
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