共查询到19条相似文献,搜索用时 62 毫秒
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基于等价相异度矩阵的聚类 总被引:5,自引:0,他引:5
本文介绍了等价相异度矩阵的性质,证明了[d(i,j)]n-1 n×n是等价相异度矩阵,并给出了等价相异矩阵的逐次平方求解方法和基于相异度矩阵的聚类方法.最后通过实验证明了此聚类方法的可行性和有效性. 相似文献
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一种基于密度函数的直觉模糊聚类初始化方法 总被引:2,自引:0,他引:2
针对基于目标函数的直觉模糊聚类方法容易陷于局部最优值的问题,提出了一种改进的密度函数初始化方法.该方法首先利用样本密度函数在较高局部密度的区域中选取c个样本,然后遍历剩余样本进行粗归类,并计算每类各维数据的平均值作为初始聚类中心.最后通过典型实例验证,该方法不仅解决了容易陷入局部极小值的问题,同时迭代次数减少,收敛速度加快,提高了聚类性能. 相似文献
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直觉模糊C-均值聚类算法研究 总被引:2,自引:0,他引:2
鉴于直觉模糊集理论作为模糊理论的推广已得到广泛的应用,研究了将模糊C-均值聚类推广为直觉模糊C-均值聚类(IFCM)的途径和方法,分析了现有的几种IFCM算法,并提出了一种基于直觉模糊集的模糊C-均值聚类算法.该算法首先定义了直觉模糊集之间的距离;然后构造了聚类的目标函数;最后给出了聚类算法步骤.将算法用于目标识别,实验结果表明了算法的有效性. 相似文献
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针对已有基于直觉模糊集的聚类方法的局限性,提出了一种基于加权直觉模糊集合的聚类模型——WIFSCM。在该模型中,提出了特定特征空间下的等价样本和加权直觉模糊集合的概念;并推导出基于等价样本和加权直觉模糊集合的直觉模糊聚类算法的目标函数,利用该目标函数推导出直觉模糊聚类中心迭代算法和隶属度矩阵迭代算法;定义了基于加权直觉模糊集合的密度函数,确定了初始聚类中心,减少了迭代次数。通过灰度图像分割实验,证明了该模型的有效性,同时与普通直觉模糊集FCM聚类算法(IFCM)相比,聚类速度提高近百倍。 相似文献
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针对现有直觉模糊聚类方法大都未考虑属性(指标)权重,计算过于复杂且计算结果为实数的问题,提出一种基于新直觉模糊相似度的聚类方法,计算结果为直觉模糊数,运用直觉模糊熵得到属性权重,构造了一种考虑属性权重的直觉模糊相似度公式,得到直觉模糊相似矩阵,设计了风险参数,决策者根据自己风险偏好选择风险参数进行聚类.最后通过算例验证了所提出方法的可行性和合理性. 相似文献
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针对直觉模糊群决策问题,依据专家的直觉模糊评价信息,利用直觉模糊相似度和相异度构造直觉模糊相似矩阵,为了得到合理的专家聚类结果,设计风险参数并提出聚类阈值变化率分析方法,综合聚类结果和直觉模糊熵对各专家进行组合赋权。提出基于离散正态分布的位置权重确定方法,构造直觉模糊集混合加权集结算子对各专家关于方案集的直觉模糊评价信息进行综合集成。结合算例验证了方法的可行性和有效性。 相似文献
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基于直觉模糊ART神经网络的群事件检测方法 总被引:1,自引:0,他引:1
描述了态势评估系统中的目标编群问题、目标群处理流程和群事件的检测。结合直觉模糊贴近度理论,构造了直觉模糊ART神经网络。设计了网络的运行机制和网络权值向量的学习机制。给出了一个具体实例,检验了直觉模糊ART神经网络的目标编群效果,为群事件检测提供了一条有效途径。 相似文献
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构造并系统研究了直觉模糊T模的剩余蕴涵。在此基础上,推导出了直觉模糊粗糙集的一种构造模型,证明了Pawlak粗糙集、直觉模糊集、模糊粗糙集、粗糙模糊集及模糊T粗糙集都是直觉模糊粗糙集的特殊情形。最后给出并证明了直觉模糊粗糙集的一些性质。 相似文献
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李毅 《电脑与微电子技术》2014,(19):3-8
聚类分析即将一组事物根据其性质上亲疏远近的程度进行分类,把性质相近的个体归为一类,使得同一类中的个体具有高度的同质性,不同类之间的个体具有高度的异质性。模糊聚类分析是现今模糊理论应用最广泛和最富成果的技术之一。阐述模糊聚类的理论,以部分石油股票为例,抽取影响石油股票收益因素的数据,利用最大最小法建立相似矩阵,用传递闭包法作出聚类分析,并进行总结。 相似文献
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In this paper, we show how one can take advantage of the stability and effectiveness of object data clustering algorithms when the data to be clustered are available in the form of mutual numerical relationships between pairs of objects. More precisely, we propose a new fuzzy relational algorithm, based on the popular fuzzy C-means (FCM) algorithm, which does not require any particular restriction on the relation matrix. We describe the application of the algorithm to four real and four synthetic data sets, and show that our algorithm performs better than well-known fuzzy relational clustering algorithms on all these sets. 相似文献
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This research addresses system reliability analysis using weakest t-norm based approximate intuitionistic fuzzy arithmetic operations, where failure probabilities of all components are represented by different types of intuitionistic fuzzy numbers. Due to the incomplete, imprecise, vague and conflicting information about the component of system, the present study evaluates the reliability of system in terms of membership function and non-membership function by using weakest t-norm (Tw) based approximate intuitionistic fuzzy arithmetic operations on different types of intuitionistic fuzzy numbers. In general, interval arithmetic (α-cut arithmetic) operations have been used to analyze the fuzzy system reliability. In complicated systems, interval arithmetic operations may occur the accumulating phenomenon of fuzziness. In order to overcome the accumulating phenomenon of fuzziness, this research adopts approximate intuitionistic fuzzy arithmetic operations under the weakest t-norm arithmetic operations (Tw) to analyze fuzzy system reliability. The approximate intuitionistic fuzzy arithmetic operations employ principle of interval arithmetic under the weakest t-norm arithmetic operations. The proposed novel fuzzy arithmetic operations may obtain fitter decision values, which have smaller fuzziness accumulating and successfully analyze the system reliability. Also weakest t-norm arithmetic operations provide more exact fuzzy results and effectively reduce fuzzy spreads (fuzzy intervals). Using proposed approach, fuzzy reliability of series system and parallel system are also constructed. For numerical verification of proposed approach, a malfunction of printed circuit board assembly (PCBA) is presented as a numerical example. The result of the proposed method is compared with the listing approaches of reliability analysis methods. 相似文献
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This paper presents a general framework for the study of relation-based (I,T)-intuitionistic fuzzy rough sets by using constructive and axiomatic approaches. In the constructive approach, by employing an intuitionistic fuzzy implicator I and an intuitionistic fuzzy triangle norm T, lower and upper approximations of intuitionistic fuzzy sets with respect to an intuitionistic fuzzy approximation space are first defined. Properties of (I,T)-intuitionistic fuzzy rough approximation operators are examined. The connections between special types of intuitionistic fuzzy relations and properties of intuitionistic fuzzy approximation operators are established. In the axiomatic approach, an operator-oriented characterization of (I,T)-intuitionistic fuzzy rough sets is proposed. Different axiom sets characterizing the essential properties of intuitionistic fuzzy approximation operators associated with various intuitionistic fuzzy relations are explored. 相似文献
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针对传统图像边缘检测算法抑制噪声能力差的问题,提出一种基于直觉模糊集(Intuitionistic Fuzzy Set,IFS)的边缘检测算法。该算法设定了一个表示平坦区域的模板图像,并在图像窗口内构造了一种同时考虑了图像梯度和图像窗口的方差信息的隶属度函数,然后通过计算图像窗口与模板图像之间的模糊直觉散度(Intuitionistic Fuzzy Divergence,IFD)对边缘进行定位和输出。实验结果表明,对于被高斯噪声或均匀噪声严重污染的图像,该算法能够得到较好的检测结果。 相似文献