The reduction and fusion of fuzzy covering systems based on the evidence theory

  • Authors:

  • Tao Feng;Shao-Pu Zhang;Ju-Sheng Mi

  • Affiliations:

  • College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050016, China and College of Science, Hebei University of Science and Technology, Shijiazhuang 050018, China;Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China;College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050016, China

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2012

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Abstract

This paper studies reduction of a fuzzy covering and fusion of multi-fuzzy covering systems based on the evidence theory and rough set theory. A novel pair of belief and plausibility functions is defined by employing a method of non-classical probability model and the approximation operators of a fuzzy covering. Then we study the reduction of a fuzzy covering based on the functions we presented. In the case of multiple information sources, we present a method of information fusion for multi-fuzzy covering systems, by which objects can be well classified in a fuzzy covering decision system. Finally, by using the method of maximum flow, we discuss under what conditions, fuzzy covering approximation operators can be induced by a fuzzy belief structure.