Search Results - Fuzzy-c regression clustering

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

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

“…This paper proposes a new type-2 fuzzy c-regression clustering algorithm for the structure identification phase of Takagi–Sugeno (T–S) systems…”
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Incremental Fuzzy C-Regression Clustering From Streaming Data for Local-Model-Network Identification by Blazic, Saso, Skrjanc, Igor

“…In this paper, a new approach to evolving fuzzy model identification from streaming data is given. The structure of the model is given as a local model network…”
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FCM-RDpA: TSK fuzzy regression model construction using fuzzy C-means clustering, regularization, Droprule, and Powerball Adabelief by Shi, Zhenhua, Wu, Dongrui, Guo, Chenfeng, Zhao, Changming, Cui, Yuqi, Wang, Fei-Yue

“…) algorithm was recently proposed. This paper further proposes FCM-RDpA, which improves MBGD-RDA by replacing the grid partition approach in rule initialization by fuzzy c-means clustering, and AdaBound by Powerball AdaBelief…”
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Hybrid System Identification by Incremental Fuzzy C-regression Clustering by Blazic, Saso, Skrjanc, Igor

“…In this paper, an approach to the identification of hybrid systems is discussed. It is based on the incremental fuzzy C-regression clustering…”
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Interval Fuzzy c-Bivariate Regression Models with Box–Cox Transformation Clustering Approach for the Interval-Valued Data by Jeng, Jin-Tsong, Chuang, Chen-Chia, Lin, Tzu-Yun

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Fuzzy Ordered c-Means Clustering and Least Angle Regression for Fuzzy Rule-Based Classifier: Study for Imbalanced Data by Leski, Jacek M., Czabanski, Robert, Jezewski, Michal, Jezewski, Janusz

“…This article introduces a new classifier design method that is based on a modification of the traditional fuzzy clustering…”
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A fuzzy C‐regression model algorithm using a new PSO algorithm by Taieb, Adel, Soltani, Moez, Chaari, Abdelkader

“… Finally, comparative experiments are designed to verify the validity of the proposed clustering algorithm and the Takagi…”
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A Study of Support Vector Regression-Based Fuzzy c -Means Algorithm on Incomplete Data Clustering by Shi, Maolin, Wang, Zihao

“…Support vector regression-based fuzzy c -means algorithm (SVR-FCM) clusters data according to their relationship among attributes, which can provide competitive…”
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Forecasting ground vibration due to rock blasting: a hybrid intelligent approach using support vector regression and fuzzy C-means clustering by Sheykhi, Hasan, Bagherpour, Raheb, Ghasemi, Ebrahim, Kalhori, Hamid

“…) and fuzzy C-means clustering (FCM). The model is developed based on blasting data compiled from Sarcheshmeh copper mine, Iran…”
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Bankruptcy forecasting: A hybrid approach using Fuzzy c-means clustering and Multivariate Adaptive Regression Splines (MARS) by De Andrés, Javier, Lorca, Pedro, de Cos Juez, Francisco Javier, Sánchez-Lasheras, Fernando

“…% of the companies went bankrupt. ► The present research presents a hybrid approach using fuzzy c-means clustering and Multivariate Adaptive Regression Splines…”
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Fuzzy C-Regression Clustering Algorithm Based 7-Dof Redundant Manipulators Inverse Dynamics Control by Zhao, Jiayu, Zhao, Tao, Yang, Hainan, Pan, Jianhui

“… To address this challenge, we propose a data-driven approach using the interval type-2 (IT2) fuzzy c-regression clustering…”
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Fuzzy weighted c-harmonic regressions clustering algorithm by Zhao, Yang, Wang, Pei-hong, Li, Yi-guo, Li, Meng-yang

“…As a well-known regression clustering algorithm, fuzzy c -regressions (FCR) has been widely studied and applied in various areas…”
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Interacting T-S fuzzy particle filter algorithm for transfer probability matrix of adaptive online estimation model by Wang, Xiao-li, Xie, Wei-xin, Li, Liang-qun

“…•The proposed algorithm can be regarded as a switching dynamical model.•A fuzzy C-regression clustering method based on maximum correntropy principle and spatial-temporal information is proposed…”
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Streamflow Forecasting and Estimation Using Least Square Support Vector Regression and Adaptive Neuro-Fuzzy Embedded Fuzzy c-means Clustering by Kisi, Ozgur

“…This paper investigates the ability of least square support vector regression (LSSVR) and adaptive neuro-fuzzy embedded fuzzy c-means clustering…”
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Dynamic Type-2 Fuzzy Dependent Dirichlet Regression Mixture clustering model by Gamasaee, R., Zarandi, M.H. Fazel

“…) technique and Interval Type-2 Fuzzy C-regression Clustering Model (IT2FCRM). DDPM method demonstrates that the probability of assigning data to a cluster including…”
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A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method by Zhou, Xiangbing, Miao, Fang, Ma, Hongjiang, Zhang, Hua, Gong, Huaming

“…++ are integrated in fuzzy C-means (FCM) clustering, which are used to maintain the stability and the robustness of the clustering process…”
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Interval type-2 modified fuzzy c-regression model clustering algorithm in TS Fuzzy Model identification by Dam, Tanmoy, Deb, Alok Kanti

“…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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A novel recursive T-S fuzzy semantic modeling approach for discrete state-space systems by Li, Liang-Qun, Wang, Xiao-Li, Xie, Wei-Xin, Liu, Zong-Xiang

“…•Fuzzy correntropy is constructed.•A novel kernel fuzzy C-regression model clustering based on fuzzy correntropy is proposed…”
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Block Sparse Representations in Modified Fuzzy C-Regression Model Clustering Algorithm for TS Fuzzy Model Identification by Dam, Tanmoy, Deb, Alok

“…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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