Complex dual hesitant fuzzy set (CDHFS) is an assortment of complex fuzzy set (CFS) and dual hesitant fuzzy set (DHFS). In this manuscript, the notion of the CDHFS is explored and its operational laws are discussed. The new methodology of the complex interval-valued dual hesitant fuzzy set (CIvDHFS) and its necessary laws are introduced and are also defensible with the help of examples. Further, the antilogarithmic and with-out exponential-based similarity measures, generalized similarity measures, and their important characteristics are also developed. These similarity measures are applied in the environment of pattern recognition and medical diagnosis to evaluate the proficiency and feasibility of the established measures. We also solved some numerical examples using the established measures to examine the reliability and validity of the proposed measures by comparing these with existing measures. To strengthen the proposed study, the comparative analysis is made and it is conferred that the proposed study is much more superior to the existing studies.

中文翻译：

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复杂双重犹豫模糊集的一种新方法及其在模式识别和医学诊断中的应用

复杂双重犹豫模糊集（CDHFS）是复杂模糊集（CFS）和双重犹豫模糊集（DHFS）的分类。在本手稿中，探讨了CDHFS的概念并讨论了其运行规律。介绍了复数区间值双重犹豫模糊集（CIvDHFS）的新方法及其必要的定律，并且在示例的帮助下也是可辩护的。此外，还开发了反对数和无指数相似性度量，广义相似性度量及其重要特征。将这些相似性措施应用于模式识别和医学诊断环境中，以评估所建立措施的熟练程度和可行性。我们还使用已建立的方法解决了一些数值示例，通过将它们与现有方法进行比较来检验所提出方法的可靠性和有效性。为了加强拟议的研究，进行了比较分析，并认为拟议的研究要优于现有的研究。