Results 21 to 30 of about 867,994 (193)
Dealing with non-metric dissimilarities in fuzzy central clustering algorithms [PDF]
, 2008 Clustering is the problem of grouping objects on the basis of a similarity measure among them. Relational clustering methods can be employed when a feature-based representation of the objects is not available, and their description is given in terms of ...
Filippone, Maurizio +2 more
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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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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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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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A new Semi-Supervised Intuitionistic Fuzzy C-means Clustering [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2020 Semi-supervised clustering algorithms aim to increase the accuracy of unsupervised clustering process by effectively exploring the limited supervision available in the form of labelled data.
J. Arora, M. Tushir
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Fuzzy clustering of time series gene expression data with cubic-spline [PDF]
, 2013 Data clustering techniques have been applied to ex- tract information from gene expression data for two decades. A large volume of novel clustering algorithms have been developed and achieved great success.
Ali, Akhtar, Wang, Yu, Angelova, Maia
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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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Clustering as a tool for self-generation of intelligent systems : a survey. [PDF]
, 2010 Fuzzy Rule Based (FRB) and Neuro-fuzzy systems are commonly used as a basis for intelligent systems due to their transparent and simple human interpretable structure.
Angelov, Plamen, Dutta Baruah, Rashmi
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Clustering stock price volatility using intuitionistic fuzzy sets [PDF]
, 2022 Clustering involves gathering a collection of objects into homogeneous groups or clusters, such that objects in the same cluster are more similar when compared to objects present in other groups.
Chountas, P., Urumov, G.
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