Výsledky vyhledávání - fuzzy C‐regression model clustering algorithm~

  1. 1

    T–S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm Autor Li, Chaoshun, Zhou, Jianzhong, Xiang, Xiuqiao, Li, Qingqing, An, Xueli

    ISSN: 0952-1976, 1873-6769
    Vydáno: Elsevier Ltd 01.06.2009
    “…This paper proposes a novel approach for identification of Takagi–Sugeno (T–S) fuzzy model, which is based on a new fuzzy c-regression model (FCRM…”
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  2. 2

    A fuzzy Cregression model algorithm using a new PSO algorithm Autor Taieb, Adel, Soltani, Moez, Chaari, Abdelkader

    ISSN: 0890-6327, 1099-1115
    Vydáno: Bognor Regis Wiley Subscription Services, Inc 01.01.2018
    “…‐output local linear Takagi‐Sugeno fuzzy models using the weighted recursive least squares (WRLS…”
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  3. 3

    A type-2 fuzzy c-regression clustering algorithm for Takagi–Sugeno system identification and its application in the steel industry Autor Fazel Zarandi, M.H., Gamasaee, R., Turksen, I.B.

    ISSN: 0020-0255, 1872-6291
    Vydáno: Elsevier Inc 15.03.2012
    Vydáno v Information sciences (15.03.2012)
    “… The Gaussian Mixture model is used to create the partition matrix of the fuzzy c-regression clustering algorithm…”
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  4. 4

    Interval type-2 modified fuzzy c-regression model clustering algorithm in TS Fuzzy Model identification Autor Dam, Tanmoy, Deb, Alok Kanti

    Vydáno: IEEE 01.07.2016
    “…This paper introduces an interval type-2 modified fuzzy c-regression model (IT2MFCRM) clustering algorithm for identifying the structure in TS Fuzzy Model…”
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  5. 5

    Block Sparse Representations in Modified Fuzzy C-Regression Model Clustering Algorithm for TS Fuzzy Model Identification Autor Dam, Tanmoy, Deb, Alok

    ISBN: 1479975605, 9781479975600
    Vydáno: IEEE 01.12.2015
    “…A novel objective function based clustering algorithm has been introduced by considering linear functional relation between input-output data and geometrical shape of input data…”
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  6. 6

    Takagi-Sugeno fuzzy model parameters identification based on fuzzy c-regression model clustering algorithm and particle swarm optimization Autor Soltani, Moez, Chaari, Abdelkader, Ben Hmida, Faycal

    ISBN: 9781467307826, 1467307823
    ISSN: 2158-8473
    Vydáno: IEEE 01.03.2012
    “… This new approach combines the advantages of fuzzy c-regression model clustering algorithm and particle swarm optimization…”
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  7. 7

    Intuitionistic fuzzy C-regression by using least squares support vector regression Autor Lin, Kuo-Ping, Chang, Hao-Feng, Chen, Tung-Lian, Lu, Yu-Ming, Wang, Ching-Hsin

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 01.12.2016
    Vydáno v Expert systems with applications (01.12.2016)
    “…•The novel clustering algorithm improves conventional fuzzy c-regression model.•Empirical results indicate that the proposed clustering algorithm has superior performance…”
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  8. 8

    The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm Autor Chung-Chun Kung, Shuo-Chieh Chang

    ISBN: 9781457706523, 1457706520
    ISSN: 1062-922X
    Vydáno: IEEE 01.10.2011
    “…In this paper, the estimation of the state of charge (SOC) of lithium-ion battery by fuzzy c-regression model (FCRM…”
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  9. 9

    Hysteresis Modeling of Piezoelectric Actuators Based on a T-S Fuzzy Model Autor Yang, Liu, Wang, Qingtao, Xiao, Yongqiang, Li, Zhan

    ISSN: 2079-9292, 2079-9292
    Vydáno: Basel MDPI AG 01.09.2022
    Vydáno v Electronics (Basel) (01.09.2022)
    “… Firstly, an improved fuzzy c regression clustering algorithm is proposed to identify the antecedent parameters of T-S fuzzy model…”
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  10. 10

    A modified fuzzy c-regression model clustering algorithm for T-S fuzzy model identification Autor Soltani, M, Aissaoui, B, Chaari, A, Ben Hmida, Faycal, Gossa, M

    ISBN: 9781457704130, 1457704137
    Vydáno: IEEE 01.03.2011
    “…In this paper, a modified fuzzy c-regression model (FCRM) clustering algorithm for identification of Takagi-Sugeno…”
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  11. 11

    Hydraulic turbine governing system identification using T–S fuzzy model optimized by chaotic gravitational search algorithm Autor Li, Chaoshun, Zhou, Jianzhong, Xiao, Jian, Xiao, Han

    ISSN: 0952-1976, 1873-6769
    Vydáno: Elsevier Ltd 01.10.2013
    “…) is proposed and applied in the modeling of HTGS. In the proposed method, fuzzy c-regression model clustering algorithm is used to partition the input space and identify the coarse antecedent membership function (MF…”
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  12. 12

    An Approach Towards the Design of Interval Type-3 T-S Fuzzy System Autor Singh, Dhanjeet, Verma, Nishchal, Ghosh, Ajoy, Malagaudanavar, Appasaheb

    ISSN: 1063-6706, 1941-0034
    Vydáno: New York IEEE 01.09.2022
    Vydáno v IEEE transactions on fuzzy systems (01.09.2022)
    “…This article providesa systematic approach for the design of an interval type-3 (IT3) Takagi-Sugeno (T-S) fuzzy logic system…”
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  13. 13

    A study of cluster validity criteria for the fuzzy c-regression models clustering algorithm Autor Chung-Chun Kung, Jui-Yiao Su

    ISBN: 142440990X, 9781424409907
    ISSN: 1062-922X
    Vydáno: IEEE 01.10.2007
    “…The fuzzy c-regression models (FCRM) clustering algorithm can fit data to locally regression models which are linear in their parameters and be used as a tool to the identification of complex nonlinear systems…”
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  14. 14

    Adaptive Inverse Controller Design Based on the Fuzzy C-Regression Model (FCRM) and Back Propagation (BP) Algorithm Autor Jian Zhong, Shi

    ISSN: 2078-2489, 2078-2489
    Vydáno: Basel MDPI AG 01.12.2019
    Vydáno v Information (Basel) (01.12.2019)
    “… Since the consequent parameters of T-S fuzzy models are linear expressions, this paper firstly uses a fuzzy c-regression model (FCRM…”
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  15. 15

    Characterization and prediction of the backscattered form function of an immersed cylindrical shell using hybrid fuzzy clustering and bio-inspired algorithms Autor Agounad, Said, Aassif, El Houcein, Khandouch, Younes, Maze, Gérard, Décultot, Dominique

    ISSN: 0041-624X, 1874-9968, 1874-9968
    Vydáno: Netherlands Elsevier B.V 01.02.2018
    Vydáno v Ultrasonics (01.02.2018)
    “…•Improving fuzzy clustering models using bio-inspired algorithms.•Comparing the performance of hybrid fuzzy clustering and bio-inspired algorithms…”
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  16. 16

    A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model Autor Güler Dincer, Nevin

    ISSN: 1562-2479, 2199-3211
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2018
    “…This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF…”
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  17. 17

    Hybrid robust approach for TSK fuzzy modeling with outliers Autor Chuang, Chen-Chia, Jeng, Jin-Tsong, Tao, Chin-Wang

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 01.07.2009
    Vydáno v Expert systems with applications (01.07.2009)
    “… The approach consists of a robust fuzzy C-regression model (RFCRM) clustering algorithm in the coarse-tuning phase and an annealing robust back-propagation (ARBP…”
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  18. 18

    A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization Autor Soltani, Moêz, Chaari, Abdelkader, Ben Hmida, Fayçal

    ISSN: 1641-876X, 2083-8492, 2083-8492
    Vydáno: Zielona Góra Versita 01.09.2012
    “…This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM…”
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    On robust fuzzy c-regression models Autor Leski, Jacek M., Kotas, Marian

    ISSN: 0165-0114, 1872-6801
    Vydáno: Elsevier B.V 15.11.2015
    Vydáno v Fuzzy sets and systems (15.11.2015)
    “… Its generalization by application of hyperplane shaped prototypes of the clusters is known as the Fuzzy C-Regression Models (FCRM) method…”
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    A new approach to fuzzy modeling Autor Kim, Euntai, Park, Minkee, Ji, Seunghwan, Park, Mignon

    ISSN: 1063-6706
    Vydáno: IEEE 01.08.1997
    Vydáno v IEEE transactions on fuzzy systems (01.08.1997)
    “…: coarse tuning and fine tuning. In coarse tuning, fuzzy C-regression model (FCRM) clustering is used, which is a modified version of fuzzy C-means (FCM…”
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