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多粒度模糊粗糙近似算子的信任结构与属性约简 被引量:5

The fuzzy belief structure and attribute reduction based on multi-granulation fuzzy rough operators
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摘要 多粒度是近年来粗糙集领域研究的一个热点方向,为使多粒度模型更适用于实际数据,提高模型的可用性,模糊思想被引入到多粒度粗糙集模型中。本文构建了基于模糊相似关系下的多粒度模糊粗糙集模型,并建立了模糊信任结构。在该信任结构下根据多粒度模糊粗糙集的上、下近似构造信任函数与似然函数。研究多粒度模糊粗糙集在模糊等价关系下的属性约简,并给出相关算法。 Multi-granulation is a hot direction in rough set theory. To make multi-granulation model more applicable to practical data, and to improve the usability of the model, the fuzzy concept is employed in multi-granulation model. A multi-granulation fuzzy rough set model is constructed based on fuzzy similarity relation, and a fuzzy belief structure is established. The belief function and probability function are constructed based on the upper and lower approximations of the multi-granulation fuzzy rough set under the trust structure. An attribute reduction of multi-granulation fuzzy rough sets is explored under fuzzy equivalence relation, and a reduction algorithm is formulated.
出处 《山东大学学报(理学版)》 CAS CSCD 北大核心 2017年第7期30-36,共7页 Journal of Shandong University(Natural Science)
基金 国家自然科学基金资助项目(61573127 61502144 61300121 61472463) 河北省自然科学基金资助项目(A2014205157) 河北省高校创新团队领军人才培育计划项目(LJRC022) 河北省博士后择优资助科研项目(B2016003013) 河北省高校自然科学基金资助项目(QN2016133) 河北师范大学博士科学基金资助项目(L2015B01) 河北师范大学研究生创新项目资助 河北省教育厅研究生创新项目(sj2015001)
关键词 多粒度 模糊粗糙集 信任函数 似然函数 属性约简 multi-granulation rough fuzzy set belief function probability function attribute reduction
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