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A robust multi-view knowledge transfer-based rough fuzzy C-means clustering algorithm
Rough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlap** and uncertainty of data....
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Optimizing kernel possibilistic fuzzy C-means clustering using metaheuristic algorithms
Over the past decade, metaheuristic algorithms have gained significant attention from researchers due to their effectiveness and computational...
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Weighted Intuitionistic Fuzzy C-Means Clustering Algorithms
Atanassov intuitionistic fuzzy set (AIFS)-based C -means algorithms are successful in clustering uncertain or vague real-world datasets. The...
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Parallel Fuzzy C-Means Clustering Based Big Data Anonymization Using Hadoop MapReduce
The amount of data on the internet is steadily growing due to recent technological advancements in cyber-physical-social systems, sensor networks,...
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Patch-Based Fuzzy Local Weighted C-Means Clustering Algorithm with Correntropy Induced Metric for Noise Image Segmentation
Fuzzy clustering is widely used in image segmentation because of its ability to describe the uncertain information presented in images. However,...
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A novel enhancement-based rapid kernel-induced intuitionistic fuzzy c-means clustering for brain tumor image
Soft clustering techniques are extensively used for segmenting medical images, and in particular, fuzzy c-means (FCM) clustering is employed to...
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Fuzzy C-means Clustering Image Segmentation Algorithm Based on Hidden Markov Model
Aiming at the poor anti-jamming effect of traditional fuzzy c-means clustering image segmentation method, a fuzzy c-means clustering image...
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INCM: neutrosophic c-means clustering algorithm for interval-valued data
Data clustering has emerged as a prospective technique for analyzing interval-valued data and has found extensive applications across various...
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Fuzzy C-Means and Fuzzy Cheetah Chase Optimization Algorithm
Clustering problems with multiclasses and ambiguities have been handled by fuzzy clustering for decades in real-world applications. Among the most...
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Dynamic customer segmentation: a case study using the modified dynamic fuzzy c-means clustering algorithm
Dynamic customer segmentation (DCS) is a useful tool for managers to adjust their marketing strategies from time to time. However, no study in the...
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COVID-19 Data Clustering Using K-means and Fuzzy c-means Algorithm
Corona Virus Disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory symptoms. It has been declared a global pandemic...
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A personalized recommendation system for teaching resources in sports using fuzzy C-means clustering technique
Due to the fast-growing Internet speed, processing power, and the use of sophisticated algorithms, information is generated at a very fast speed....
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Hybrid multi-objective metaheuristic and possibilistic intuitionistic fuzzy c-means algorithms for cluster analysis
This study proposes a hybrid multi-objective meta-heuristics and possibilistic intuitionistic fuzzy c -means (PIFCM) algorithms for cluster analysis....
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Modified fuzzy clustering algorithm based on non-negative matrix factorization locally constrained
The fuzzy C-means (FCM) algorithm is a classical clustering algorithm which is widely used. However, especially for high-dimensional data sets with...
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Assessing the efficacy of a novel adaptive fuzzy c-means (AFCM) based clustering algorithm for mobile agent itinerary planning in wireless sensor networks using validity indices
Wireless Sensor Networks (WSN) are composed of small sensor nodes that either transmit their sensed data to the sink node directly or transmit it to...
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Fuzzy C-Means Clustering Validity Function Based on Multiple Clustering Performance Evaluation Components
Clustering is the process of grou** a set of physical or abstract objects into multiple similar objects. Fuzzy C-means (FCM) clustering is one of...
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Gaussian-Kernel Neutrosophic C-Means Clustering
Fuzzy c-means (FCM) clustering is an extension of k-means based on the truth membership function of fuzzy sets. Neutrosophic sets extended fuzzy sets...
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A novel type-II intuitionistic fuzzy clustering algorithm for mammograms segmentation
Fuzzy clustering has been gaining prominence in medical image segmentation but challenges still exist. This paper proposes a novel Type-II...
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A Bi-directional Fuzzy C-Means Clustering Ensemble Algorithm Considering Local Information
The classic Fuzzy C-means (FCM) algorithm has limited clustering performance and is prone to misclassification of border points. This study offers a...
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MapReduce-based Fuzzy C-means Algorithm for Distributed Document Clustering
The clustering of big data is a challenging task. The traditional clustering algorithms are inefficient for clustering big data. The recent...
