期刊文献+

Entropy measures of type-2 intuitionistic fuzzy sets and type-2 triangular intuitionistic trapezodial fuzzy sets 被引量:2

Entropy measures of type-2 intuitionistic fuzzy sets and type-2 triangular intuitionistic trapezodial fuzzy sets
下载PDF
导出
摘要 In order to measure the uncertain information of a type-2 intuitionistic fuzzy set(T2IFS), an entropy measure of T2 IFS is presented by using the constructive principles. The proposed entropy measure is also proved to satisfy all of the constructive principles. Further, a novel concept of the type-2 triangular intuitionistic trapezoidal fuzzy set(T2TITr FS) is developed, and a geometric interpretation of the T2 TITr FS is given to comprehend it completely or correctly in a more intuitive way. To deal with a more general uncertain complex system, the constructive principles of an entropy measure of T2 TITr FS are therefore proposed on the basis of the axiomatic definition of the type-2 intuitionisic fuzzy entropy measure. This paper elicits a formula of type-2 triangular intuitionistic trapezoidal fuzzy entropy and verifies that it does satisfy the constructive principles. Two examples are given to show the efficiency of the proposed entropy of T2 TITr FS in describing the uncertainty of the type-2 intuitionistic fuzzy information and illustrate its application in type-2 triangular intuitionistic trapezodial fuzzy decision making problems. In order to measure the uncertain information of a type- 2 intuitionistic fuzzy set (T21FS), an entropy measure of T21FS is presented by using the constructive principles. The proposed entropy measure is also proved to satisfy all of the constructive principles. Further, a novel concept of the type-2 triangular in- tuitionistic trapezoidal fuzzy set (T2TITrFS) is developed, and a geometric interpretation of the T2TITrFS is given to comprehend it completely or correctly in a more intuitive way. To deal with a more general uncertain complex system, the constructive principles of an entropy measure of T2TITrFS are therefore proposed on the basis of the axiomatic definition of the type-2 intuitionisic fuzzy entropy measure. This paper elicits a formula of type-2 triangular intuitionistic trapezoidal fuzzy entropy and verifies that it does sa- tisfy the constructive principles. Two examples are given to show the efficiency of the proposed entropy of T2TITrFS in describing the uncertainty of the type-2 intuitionistic fuzzy information and illustrate its application in type-2 triangular intuitionistic trapezodial fuzzy decision making problems.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第4期774-793,共20页 系统工程与电子技术(英文版)
基金 supported by the National Natural Science Foundation of China(71371156 70971017) the Research Grants Council of the Hong Kong Special Administrative Region,China(City U112111)
关键词 直觉模糊集 模糊熵 三角 2型 不确定性信息 公理化定义 几何解释 复杂系统 type-2 intuitionistic fuzzy set, intuitionistic fuzzy en-tropy, type-2 triangular intuitionistic trapezoidal fuzzy entropy.
  • 相关文献

参考文献1

二级参考文献20

  • 1刘锋,袁学海.模糊数直觉模糊集[J].模糊系统与数学,2007,21(1):88-91. 被引量:84
  • 2ZADEH L A. Fuzzy sets [J]. Information and Control, 1965, 8(13): 338-356.
  • 3ZADEH L A. The concept of linguistic variable and its application to approximate reasoning [J]. Information Science, 1975, 8(2): 199 - 249.
  • 4DURAN K, BERNAL H, MELGAREJO M. Improved iterative al- gorithm for computing the generalized centroid of an interval type-2 fuzzy set [C] //Proceedings of the 2008 Annual Meeting of the North American Fuzzy Information Processing Society. New York: IEEE, 2008:1 - 6.
  • 5COUPLAND S, JOHN R. Geometric type-1 and type-2 fuzzy logic systems [J]. IEEE Transactions on Fuzzy Systems, 2007, 15(1): 3 - 15.
  • 6KARNIK N N, MENDEL J M. Introduction to type-2 fuzzy logic systems [C]//Proceedings of the 1EEE World Congress on Computa- tional Intelligence. Anchorage, USA: IEEE, 1998: 915- 920.
  • 7LIANG Q, MENDEL J M. Interval type-2 fuzzy logic systems: the ory and design [J]. IEEE Transactions on Fuzzy Systems, 2000, 8(5) 535 - 550.
  • 8MENDEL J M. Uncertain Rule-Based Fuzzy Logic Systems: Intro- duction and New Directions [M]. Upper Saddle River, NJ: Prentice- Hall, 2001.
  • 9MENDEL J M. Type-2 fuzzy sets and systems: an overview [J]. IEEE Computational Intelligence Magazine, 2007, 2(1): 20 - 29.
  • 10MENDEL J M. Advance in type-2 fuzzy sets and systems [J]. Infor- mation Sciences, 2007, 177(1): 84- 110.

共引文献9

同被引文献27

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部