Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (11): 41-45.DOI: 10.3778/j.issn.1002-8331.1704-0179

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Improved rough intuitionistic fuzzy sets

WANG Jinying, WANG Yanping, QI Shuang   

  1. Science College, Liaoning University of Technology, Jinzhou, Liaoning 121001, China
  • Online:2018-06-01 Published:2018-06-14


王金英,王艳平,齐  爽   

  1. 辽宁工业大学 理学院,辽宁 锦州 121001

Abstract: In Pawlak approximation space, it tries to find a better approximation of the goals set directing at the intuitionistic fuzzy goal sets, under the case that the information granularity is a constant. On the basis of known rough intuitionistic fuzzy sets, the new upper and lower approximation operators of intuitionistic fuzzy sets are established in the form of piecewise functions according to intuitionistic rough membership functions. In addition, some basic properties of the new model are discussed. Compared with the existing rough intuitionistic fuzzy sets, there has been a great improvement both in terms of approximation accuracy and similarity degree of the goal sets for the improved models. Finally the validity of the proposed conclusions has been verified by the numerical examples.

Key words: rough intuitionistic fuzzy sets, rough membership function, approximation operators, approximate accuracy, similarity degree

摘要: 在Pawlak近似空间中,针对直觉模糊目标集合,假设在信息粒度不变的情况下,试图寻求目标集合更好的近似集。在现有的粗糙直觉模糊集的基础之上,利用直觉模糊粗糙隶属函数,采用分段函数的形式建立直觉模糊集新的下近似与上近似算子,并讨论新模型的一些基本性质。与现有的粗糙直觉模糊集相比,改进后的模型无论在近似精度方面,还是与目标集合的相似度方面,都有了较大的改善和提高。最后通过数值算例验证了所给结论的正确性。

关键词: 粗糙直觉模糊集, 粗糙隶属函数, 近似算子, 近似精度, 相似度