Search Results - "fuzzy c-means clustering algorithm"

A Novel Evolutionary Kernel Intuitionistic Fuzzy C -means Clustering Algorithm by Lin, Kuo-Ping

“…This study proposes a novel evolutionary kernel intuitionistic fuzzy c-means clustering algorithm (EKIFCM…”
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Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership Filtering by Lei, Tao, Jia, Xiaohong, Zhang, Yanning, He, Lifeng, Meng, Hongying, Nandi, Asoke K.

“…As fuzzy c-means clustering (FCM) algorithm is sensitive to noise, local spatial information is often introduced to an objective function to improve the…”
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Projected fuzzy c-means clustering algorithm with instance penalty by Wang, Jikui, Wu, Yiwen, Huang, Xueyan, Zhang, Cuihong, Nie, Feiping

“… Therefore, to address these problems, a projected fuzzy c-means clustering algorithm with instance penalty (PCIP) is proposed…”
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A Probabilistic Linguistic Three-Way Decision Method With Regret Theory via Fuzzy c-Means Clustering Algorithm by Zhu, Jinxing, Ma, Xueling, Martinez, Luis, Zhan, Jianming

“…Aiming at multiattribute decision-making (MADM) problems with probabilistic linguistic term sets (PLTSs), and considering the effective rationality of a…”
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Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development by Askari, Salar

“…•RFCM algorithm removes drawbacks of the FCM algorithm.•RFCM algorithm eliminates interactions among clusters.•RFCM algorithm is suitable for data highly…”
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A New Membership Scaling Fuzzy C-Means Clustering Algorithm by Zhou, Shuisheng, Li, Dong, Zhang, Zhuan, Ping, Rui

“…Fuzzy c-means (FCM) is one of the most frequently used methods for clustering. However, with increasing amount of data, FCM suffers from slow convergence and a…”
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CGFFCM: Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means clustering algorithm for color image segmentation by Golzari Oskouei, Amin, Hashemzadeh, Mahdi, Asheghi, Bahareh, Balafar, Mohammad Ali

“…The fuzzy c-means (FCM) algorithm is a popular method for data clustering and image segmentation. However, the main problem of this algorithm is that it is…”
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A possibilistic fuzzy c-means clustering algorithm by Pal, N.R., Pal, K., Keller, J.M., Bezdek, J.C.

“…In 1997, we proposed the fuzzy-possibilistic c-means (FPCM) model and algorithm that generated both membership and typicality values when clustering unlabeled…”
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Robust fuzzy c-means clustering algorithm with adaptive spatial & intensity constraint and membership linking for noise image segmentation by Wang, Qingsheng, Wang, Xiaopeng, Fang, Chao, Yang, Wenting

“…The fuzzy C-means (FCM) clustering method is proven to be an efficient method to segment images. However, the FCM method is not robustness and less accurate…”
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A Novel Brain MRI Image Segmentation Method Using an Improved Multi-View Fuzzy c-Means Clustering Algorithm by Hua, Lei, Gu, Yi, Gu, Xiaoqing, Xue, Jing, Ni, Tongguang

“…Background: The brain magnetic resonance imaging (MRI) image segmentation method mainly refers to the division of brain tissue, which can be divided into…”
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Unsupervised Multiview Fuzzy C-Means Clustering Algorithm by Hussain, Ishtiaq, Sinaga, Kristina P., Yang, Miin-Shen

“…The rapid development in information technology makes it easier to collect vast numbers of data through the cloud, internet and other sources of information…”
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Robust-learning fuzzy c-means clustering algorithm with unknown number of clusters by Yang, Miin-Shen, Nataliani, Yessica

“…•We construct a robust learning-based fuzzy c-means (FCM) framework, called the robust-learning FCM (RL-FCM) algorithm.•The proposed RL-FCM can automatically…”
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Fuzzy c-means clustering algorithm for directional data (FCM4DD) by Kesemen, Orhan, Tezel, Özge, Özkul, Eda

“…•A new approximation for clustering of directional data is proposed.•The proposed method is simple, fast and stable when compared to other methods.•The…”
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Kernel-based fuzzy c-means clustering algorithm based on genetic algorithm by Ding, Yi, Fu, Xian

“…Fuzzy c-means clustering algorithm (FCM) is a method that is frequently used in pattern recognition…”
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General fuzzy C-means clustering algorithm using Minkowski metric by Zhao, Kaixin, Dai, Yaping, Jia, Zhiyang, Ji, Ye

“…•A general Fuzzy C-means algorithm is proposed to cope with the case of using Minkowski metric.•The Banach contraction mapping principle is used to guide the…”
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An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation by Verma, Hanuman, Agrawal, R.K., Sharan, Aditi

“…Original and segmented simulated brain image by different algorithms: (a) axial view of original simulated T1-weighted brain image with INU=0 and 1% noise, (b)…”
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Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images by Adhikari, Sudip Kumar, Sing, Jamuna Kanta, Basu, Dipak Kumar, Nasipuri, Mita

“…•A conditional spatial fuzzy C-means (csFCM) clustering algorithm to improve the robustness of the conventional FCM algorithm is presented.•The method…”
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EM-IFCM: Fuzzy c-means clustering algorithm based on edge modification for imbalanced data by Pu, Yue, Yao, Wenbin, Li, Xiaoyong

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Modified dynamic fuzzy c-means clustering algorithm – Application in dynamic customer segmentation by Munusamy, Sivaguru, Murugesan, Punniyamoorthy

“…The dynamic customer segmentation (DCS) is a useful tool for managers in implementing marketing strategies by observing dynamic changes that are happening in…”
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A feature-weighted suppressed possibilistic fuzzy c-means clustering algorithm and its application on color image segmentation by Yu, Haiyan, Jiang, Lerong, Fan, Jiulun, Xie, Shuang, Lan, Rong

“…The possibilistic fuzzy c-means clustering (PFCM) algorithm is a hybridization of possibilistic c-means clustering (PCM) and fuzzy c-means clustering (FCM)…”
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