Výsledky vyhledávání - "fuzzy C-means clustering algorithm"

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  1. 1

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

    ISSN: 1063-6706, 1941-0034
    Vydáno: IEEE 01.10.2014
    Vydáno v IEEE transactions on fuzzy systems (01.10.2014)
    “…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 Autor Lei, Tao, Jia, Xiaohong, Zhang, Yanning, He, Lifeng, Meng, Hongying, Nandi, Asoke K.

    ISSN: 1063-6706, 1941-0034
    Vydáno: New York IEEE 01.10.2018
    Vydáno v IEEE transactions on fuzzy systems (01.10.2018)
    “…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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  3. 3

    Projected fuzzy c-means clustering algorithm with instance penalty Autor Wang, Jikui, Wu, Yiwen, Huang, Xueyan, Zhang, Cuihong, Nie, Feiping

    ISSN: 0957-4174
    Vydáno: Elsevier Ltd 01.12.2024
    Vydáno v Expert systems with applications (01.12.2024)
    “… 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 Autor Zhu, Jinxing, Ma, Xueling, Martinez, Luis, Zhan, Jianming

    ISSN: 1063-6706, 1941-0034
    Vydáno: New York IEEE 01.08.2023
    Vydáno v IEEE transactions on fuzzy systems (01.08.2023)
    “…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 Autor Askari, Salar

    ISSN: 0957-4174, 1873-6793
    Vydáno: New York Elsevier Ltd 01.03.2021
    Vydáno v Expert systems with applications (01.03.2021)
    “…•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 Autor Zhou, Shuisheng, Li, Dong, Zhang, Zhuan, Ping, Rui

    ISSN: 1063-6706, 1941-0034
    Vydáno: New York IEEE 01.09.2021
    Vydáno v IEEE transactions on fuzzy systems (01.09.2021)
    “…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 Autor Golzari Oskouei, Amin, Hashemzadeh, Mahdi, Asheghi, Bahareh, Balafar, Mohammad Ali

    ISSN: 1568-4946, 1872-9681
    Vydáno: Elsevier B.V 01.12.2021
    Vydáno v Applied soft computing (01.12.2021)
    “…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 Autor Pal, N.R., Pal, K., Keller, J.M., Bezdek, J.C.

    ISSN: 1063-6706, 1941-0034
    Vydáno: New York IEEE 01.08.2005
    Vydáno v IEEE transactions on fuzzy systems (01.08.2005)
    “…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 Autor Wang, Qingsheng, Wang, Xiaopeng, Fang, Chao, Yang, Wenting

    ISSN: 1568-4946, 1872-9681
    Vydáno: Elsevier B.V 01.07.2020
    Vydáno v Applied soft computing (01.07.2020)
    “…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 Autor Hua, Lei, Gu, Yi, Gu, Xiaoqing, Xue, Jing, Ni, Tongguang

    ISSN: 1662-453X, 1662-4548, 1662-453X
    Vydáno: Switzerland Frontiers Research Foundation 25.03.2021
    Vydáno v Frontiers in neuroscience (25.03.2021)
    “…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 Autor Hussain, Ishtiaq, Sinaga, Kristina P., Yang, Miin-Shen

    ISSN: 2079-9292, 2079-9292
    Vydáno: Basel MDPI AG 01.11.2023
    Vydáno v Electronics (Basel) (01.11.2023)
    “…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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  12. 12

    Robust-learning fuzzy c-means clustering algorithm with unknown number of clusters Autor Yang, Miin-Shen, Nataliani, Yessica

    ISSN: 0031-3203, 1873-5142
    Vydáno: Elsevier Ltd 01.11.2017
    Vydáno v Pattern recognition (01.11.2017)
    “…•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) Autor Kesemen, Orhan, Tezel, Özge, Özkul, Eda

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 01.10.2016
    Vydáno v Expert systems with applications (01.10.2016)
    “…•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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  14. 14

    Kernel-based fuzzy c-means clustering algorithm based on genetic algorithm Autor Ding, Yi, Fu, Xian

    ISSN: 0925-2312, 1872-8286
    Vydáno: Elsevier B.V 05.05.2016
    Vydáno v Neurocomputing (Amsterdam) (05.05.2016)
    “…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 Autor Zhao, Kaixin, Dai, Yaping, Jia, Zhiyang, Ji, Ye

    ISSN: 0165-1684, 1872-7557
    Vydáno: Elsevier B.V 01.11.2021
    Vydáno v Signal processing (01.11.2021)
    “…•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 Autor Verma, Hanuman, Agrawal, R.K., Sharan, Aditi

    ISSN: 1568-4946, 1872-9681
    Vydáno: Elsevier B.V 01.09.2016
    Vydáno v Applied soft computing (01.09.2016)
    “…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 Autor Adhikari, Sudip Kumar, Sing, Jamuna Kanta, Basu, Dipak Kumar, Nasipuri, Mita

    ISSN: 1568-4946, 1872-9681
    Vydáno: Elsevier B.V 01.09.2015
    Vydáno v Applied soft computing (01.09.2015)
    “…•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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    Modified dynamic fuzzy c-means clustering algorithm – Application in dynamic customer segmentation Autor Munusamy, Sivaguru, Murugesan, Punniyamoorthy

    ISSN: 0924-669X, 1573-7497
    Vydáno: New York Springer US 01.06.2020
    “…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 Autor Yu, Haiyan, Jiang, Lerong, Fan, Jiulun, Xie, Shuang, Lan, Rong

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 01.05.2024
    Vydáno v Expert systems with applications (01.05.2024)
    “…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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