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基于相似度的模糊粗糙集模型

Fuzzy Rough Set Model Based on Similarity Measure

【作者】 崔玮

【导师】 田大增; 哈明虎;

【作者基本信息】 河北大学 , 应用数学, 2008, 硕士

【摘要】 粗糙集理论是一种新的处理模糊、不精确和不确定性知识的数学工具。粗糙集模型是粗糙集理论研究的重要内容。模糊粗糙集模型是粗糙集模型的重要推广。本文基于模糊相似关系进一步讨论了模糊粗糙集模型,提出了基于相似度的模糊粗糙集模型,进一步讨论了基于模糊相似关系的模糊粗糙集的性质,给出了基于相似度的模糊粗糙集上下近似算子的定义,并讨论了其基本性质。

【Abstract】 Rough set theory is emerging as a powerful tool for dealing with vagueness, imprecise and uncertainty problems. The model of rough set is the important contents of the research of Rough set theories. The fuzzy rough set model is the important generation of Rough set model. This paper the fuzzy rough set model is further discussed based on fuzzy similar relation, and the fuzzy rough set model based on similarity measure is proposed. The properties of the fuzzy rough set model based on fuzzy similar relation are further discussed. The paper gives the concept of fuzzy rough approximation operators of the fuzzy rough set model based on similarity measure, and discusses some properties of these operators.

  • 【网络出版投稿人】 河北大学
  • 【网络出版年期】2011年 S1期
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