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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Intuitive distance for intuitionistic fuzzy sets with applications in pattern recognition
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Intuitive distance for intuitionistic fuzzy sets with applications in pattern recognition

机译：在模式识别中具有应用中的直觉模糊集的直观距离

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摘要

Distance is an important fundamental concept of the set theory. Since the intuitionistic fuzzy sets (IFSs) was put forward, distance between IFSs has been widely concerned by some researchers and many types of measures have been proposed. However, although intuitionistic fuzzy sets have the advantage of being able to consider waver (lack of knowledge), existing distance measures have not yet considered waver and most of them have counter-intuitive cases. To deal with this problem, this paper introduces the concept of intuitive distance for IFSs, which embodies the property requirements of classical distance measure and highlights the characteristics of intuitionistic fuzzy information. Then, a new intuitive distance measure for IFSs is proposed along with its proofs. After that, a comparative analysis between the intuitive distance measure and the existing distance measures is conducted based on an extended artificial benchmark test set, in which eleven pairs of single-element IFSs are used as an illustration of six typical counter-intuitive cases. Finally, the proposed distance measure is applied to deal with pattern recognition. Results show that the proposed distance does not provide any counter-intuitive cases and the waver that brought from hesitance index can be well reflected.
机译：距离是集合理论的重要基础概念。由于提出了直觉模糊集（IFSS），IFSS之间的距离被一些研究人员广泛关注，并且已经提出了许多类型的措施。然而，虽然直觉模糊集具有能够考虑动摇（缺乏知识）的优势，但是现有距离措施尚未被认为是Waver，并且大多数人都具有反向直观的情况。要解决这个问题，本文介绍了IFSS直观距离的概念，它体现了经典距离测量的属性要求，并突出了直觉模糊信息的特征。然后，提出了一种新的IFSS的直观距离测量和其证明。之后，基于扩展的人工基准测试集进行直观距离测量和现有距离测量之间的比较分析，其中11对单元素IFSS被用作六个典型的反向直观情况的图示。最后，应用了距离测量来处理模式识别。结果表明，该距离不提供任何反向直观的案例，从犹豫指数带来的波动可能会得到很好的反映。

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