Double-quantitative $γ^{\ast}-$fuzzy coverings approximation operators.
作者： Guangming Lang
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摘要: In digital-based information boom, the fuzzy covering rough set model is an important mathematical tool for artificial intelligence, and how to build bridge between theory Pawlak's becoming a hot research topic. this paper, we first present $\gamma-$fuzzy based probabilistic grade approximation operators double-quantitative operators. We also study relationships among three types of Second, propose $\gamma^{\ast}-$fuzzy coverings multi-granulation lower upper investigate these Finally, employ several examples illustrate construct approximations sets with absolute relative quantitative information.
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harvard.edu参考文章(47)
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