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区间直觉模糊粗糙集的启发式属性约简方法
引用本文:周飞飞,郑婷婷,徐小丽. 区间直觉模糊粗糙集的启发式属性约简方法[J]. 合肥学院学报(自然科学版), 2014, 0(4): 15-20
作者姓名:周飞飞  郑婷婷  徐小丽
作者单位:安徽大学数学科学学院,合肥,230601
基金项目:国家自然科学青年基金,教育部人文社会科学研究规划基金,安徽省高校省级优秀青年人才重点基金项目(2013SQRL005ZD)资助.
摘    要:属性约简是数据挖掘之中最核心的问题,是任何一个部门决策知识获取的关键技术。基于深入研究模糊粗糙理论、直觉模糊粗糙集理论在属性约简知识方面的研究成果,通过定义区间模糊粗糙集的正域、依赖度与非依赖度等相关概念,提出一种启发式区间直觉模糊粗糙集属性约简方法。结果表明:该方法在知识约简中是可行的,并且相比差别矩阵方法,能有效降低空间和时间复杂度。

关 键 词:区间直觉模糊集  正域  依赖度  非依赖度

Attribute Reduction Based on Interval Intuitionstic Fuzzy Rough Sets
ZHOU Fei-fei,ZHENG Ting-ting,XU Xiao-li. Attribute Reduction Based on Interval Intuitionstic Fuzzy Rough Sets[J]. Journal of Hefei University(Natural Sciences Edition), 2014, 0(4): 15-20
Authors:ZHOU Fei-fei  ZHENG Ting-ting  XU Xiao-li
Affiliation:(School of Mathematical Sciences, Anhui University, Hefei 230601, China)
Abstract:Attribute reduction is the most crucial problem among data mining ,which is the key technology of decision‐making knowledge acquisition .This paper studies attribute reduction theory of fuzzy rough sets theory and intuitionistic fuzzy rough sets theory .By defining the interval fuzzy rough sets , their positive fields , dependency and non‐dependency and other related concepts ,it propose a heuristic interval intuitionistic fuzzy rough set attribute reduction method .The results show that the method in knowledge reduction is feasible , which can effectively reduce space and time complexity , compared with the method of discernibility matrix .
Keywords:interval intuitionistic fuzzy rough sets  positive field  dependence  non-dependence
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