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On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition

机译:复杂勾股模糊集的一些距离度量及其在模式识别中的应用

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The concept of complex fuzzy set (CFS) and complex intuitionistic fuzzy set (CIFS) is two recent developments in the field of fuzzy set (FS) theory. The significance of these concepts lies in the fact that these concepts assigned membership grades from unit circle in plane, i.e., in the form of a complex number instead from [0, 1] interval. CFS cannot deal with information of yes and no type, while CIFS works only for a limited range of values. To deal with these kinds of problems, in this article, the concept of complex Pythagorean fuzzy set (CPFS) is developed. The novelty of CPFS lies in its larger range comparative to CFS and CIFS which is demonstrated numerically. It is discussed how a CFS and CIFS could be CPFS but not conversely. We investigated the very basic concepts of CPFSs and studied their properties. Furthermore, some distance measures for CPFSs are developed and their characteristics are studied. The viability of the proposed new distance measures in a building material recognition problem is also discussed. Finally, a comparative study of the proposed new work is established with pre-existing study and some advantages of CPFS are discussed over CFS and CIFS.
机译:复杂模糊集(CFS)和复杂直觉模糊集(CIFS)的概念是模糊集(FS)理论领域中的两个最新发展。这些概念的重要性在于以下事实:这些概念从平面中的单位圆分配成员资格等级,即以复数形式而不是从[0,1]间隔分配成员资格等级。 CFS无法处理是和否类型的信息,而CIFS仅适用于有限范围的值。为了解决这些问题,本文提出了复勾股勾股模糊集(CPFS)的概念。 CPFS的新颖性在于,与CFS和CIFS相比,其数值范围更大。讨论了CFS和CIFS如何成为CPFS,但反之则不行。我们研究了CPFS的基本概念,并研究了它们的特性。此外,针对CPFS制定了一些距离度量并研究了它们的特性。还讨论了在建筑材料识别问题中提出的新距离测量方法的可行性。最后,在已有研究的基础上,对拟议的新工作进行了比较研究,并讨论了CPFS与CFS和CIFS相比的一些优势。

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