Results 11 to 20 of about 152,595 (295)
Comparison of different strategies of utilizing fuzzy clustering in structure identification [PDF]
, 2007 Fuzzy systems approximate highly nonlinear systems by means of fuzzy "if-then" rules. In the literature, various algorithms are proposed for mining. These algorithms commonly utilize fuzzy clustering in structure identification.
Kılıç, Kemal +2 more
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A Framework of Mutual Information Kullback-Leibler Divergence based for Clustering Categorical Data
JOIV: International Journal on Informatics Visualization, 2021 Clustering is a process of grouping a set of objects into multiple clusters, so that the collection of similar objects will be grouped into the same cluster and dissimilar objects will be grouped into other clusters.
Iwan Tri Riyadi Yanto +3 more
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International Journal of Computational Intelligence Systems, 2020 In the big data background, the uncertainty of data is increasingly apparent. Multi-polar fuzzy feature of data has been more popularly used by the research community for the purpose of the classification of weighing cheating in dynamic truck scale ...
Zhenyu Lu, Xianyun Huang
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Statistical and fuzzy clustering methods and their application to clustering provinces of Iraq based on agricultural products [PDF]
AUT Journal of Mathematics and Computing, 2020 The important approaches to statistical and fuzzy clustering are reviewed and compared, and their applications to an agricultural problem based on a real-world data are investigated.
Israa Atiyah, Seyed Mahmoud Taheri
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Multimodal decision-level fusion for person authentication [PDF]
, 1999 In this paper, the use of clustering algorithms for decision-level data fusion is proposed. Person authentication results coming from several modalities (e.g., still image, speech), are combined by using fuzzy k-means (FKM), fuzzy vector quantization ...
Bors, A.G., Chatzis, V., Pitas, I.
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Unsupervised EA-Based Fuzzy Clustering for Image Segmentation
IEEE Access, 2020 This paper presents an unsupervised fuzzy clustering based on evolutionary algorithm for image segmentation. It needs no prior information about exact numbers of segments.
Mengxuan Zhang +4 more
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Approximating a similarity matrix by a latent class model: A reappraisal of additive fuzzy clustering [PDF]
, 2009 Let Q be a given n×n square symmetric matrix of nonnegative elements between 0 and 1, similarities. Fuzzy clustering results in fuzzy assignment of individuals to K clusters.
Bink, M.C.A.M. +3 more
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Frontiers in Psychology, 2014 Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous.
Jocelyn H Bolin +3 more
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Random Fuzzy Clustering Granular Hyperplane Classifier
IEEE Access, 2020 Granular computing is a method of studying human intelligent information processing, which has advantage of knowledge discovery. In this paper, we convert a classification problem of sample space into a classification problem of fuzzy clustering granular
Wei Li +5 more
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Fuzzy Equivalence Relation Clustering Method Based on Constraint Conditions [PDF]
Jisuanji gongcheng, 2017 The traditional fuzzy equivalence relation clustering method cannot clusteraccording tospecific constraints,so that the clustering results have low accuracy,anddonot meet the requirement.In order to solve this problem,based on traditional fuzzy ...
LIANG Yuan,CHE Ming
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