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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 >delta-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis
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delta-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis

机译:三角洲 - 直觉模糊集的平等:医学诊断的新近似度量和应用

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摘要

Intuitionistic fuzzy set is capable of handling uncertainty with counterpart falsities which exist in nature. Proximity measure is a convenient way to demonstrate impractical significance of values of memberships in the intuitionistic fuzzy set. However, the related works of Pappis (Fuzzy Sets Syst 39(1):111-115, 1991), Hong and Hwang (Fuzzy Sets Syst 66(3):383-386, 1994), Virant (2000) and Cai (IEEE Trans Fuzzy Syst 9(5):738-750, 2001) did not model the measure in the context of the intuitionistic fuzzy set but in the Zadeh's fuzzy set instead. In this paper, we examine this problem and propose new notions of delta-equalities for the intuitionistic fuzzy set and delta-equalities for intuitionistic fuzzy relations. Two fuzzy sets are said to be delta-equal if they are equal to an extent of delta. The applications of delta-equalities are important to fuzzy statistics and fuzzy reasoning. Several characteristics of delta-equalities that were not discussed in the previous works are also investigated. We apply the delta-equalities to the application of medical diagnosis to investigate a patient's diseases from symptoms. The idea is using delta-equalities for intuitionistic fuzzy relations to find groups of intuitionistic fuzzified set with certain equality or similar degrees then combining them. Numerical examples are given to illustrate validity of the proposed algorithm. Further, we conduct experiments on real medical datasets to check the efficiency and applicability on real-world problems. The results obtained are also better in comparison with 10 existing diagnosis methods namely De et al. (Fuzzy Sets Syst 117:209-213, 2001), Samuel and Balamurugan (Appl Math Sci 6(35):1741-1746, 2012), Szmidt and Kacprzyk (2004), Zhang et al. (Procedia Eng 29:4336-4342, 2012), Hung and Yang (Pattern Recogn Lett 25:1603-1611, 2004), Wang and Xin (Pattern Recogn Lett 26:2063-2069, 2005), Vlachos and Sergiadis (Pattern Recogn Lett 28(2):197206, 2007), Zhang and Jiang (Inf Sci 178(6):
机译:直觉模糊集能够处理与本质上存在的对应虚体的不确定性。接近度量是证明直觉模糊集中成员资格值不切实际意义的便捷方式。但是,PAPPIS的相关作品(模糊套装SYST 39(1):111-115,1991),Hong和Hwang(模糊套装SYST 66(3):383-386,1994),Virant(2000)和CAI(IEEE Trans模糊SYST 9(5):738-750,2001)没有在直觉模糊集中模拟措施,而是在Zadeh的模糊集中而来。在本文中,我们研究了这个问题,并提出了直觉模糊集和直觉模糊关系的直觉模糊集合和三角洲平等的新概念。如果它们等于Delta的程度,则据说两个模糊套是Δ等于的。三角洲相位的应用对模糊统计和模糊推理很重要。还调查了在以前的作品中未讨论的达到相等性的若干特征。我们将三角洲平等应用于医学诊断的应用,以研究患者免受症状的疾病。该想法是使用Delta-Setchitition进行直觉模糊关系,找到具有某些平等或类似程度的直觉模糊定组,然后组合它们。给出了数值例子来说明所提出的算法的有效性。此外,我们对真实医疗数据集进行实验,以检查真实问题的效率和适用性。与10个现有的诊断方法相比,所获得的结果也是更好的de等人。 (模糊套装SYST 117:209-213,2001),Samuel和Balamurugan(Appl Math SCI 6(35):1741-1746,2012),Szmidt和Kacprzyk(2004),张等人。 (程序英29:4336-4342,2012),洪和杨(Pattern Idels Lett 25:1603-1611,2004),王和辛(Pattern Idels Lett 26:2063-2069,2005),Vlachos和Sergiadis(Pattern Idits Lett 28(2):197206,2007),张和江(INF SCI 178(6):

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