Fuzzy probabilistic approximation spaces and their information measures

@article{Hu2006FuzzyPA,
  title={Fuzzy probabilistic approximation spaces and their information measures},
  author={Qinghua Hu and Zongxia Xie and Daren Yu},
  journal={IEEE Transactions on Fuzzy Systems},
  year={2006},
  volume={14},
  pages={191-201}
}
Rough set theory has proven to be an efficient tool for modeling and reasoning with uncertainty information. By introducing probability into fuzzy approximation space, a theory about fuzzy probabilistic approximation spaces is proposed in this paper, which combines three types of uncertainty: probability, fuzziness, and roughness into a rough set model. We introduce Shannon's entropy to measure information quantity implied in a Pawlak's approximation space, and then present a novel… CONTINUE READING

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