Suchergebnisse - fuzzy C‐regression model clustering algorithm

T–S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm von 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 fuzzy C‐regression model algorithm using a new PSO algorithm von Taieb, Adel, Soltani, Moez, Chaari, Abdelkader

“… ‐output local linear Takagi‐Sugeno fuzzy models using the weighted recursive least squares (WRLS …”
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A type-2 fuzzy c-regression clustering algorithm for Takagi–Sugeno system identification and its application in the steel industry von Fazel Zarandi, M.H., Gamasaee, R., Turksen, I.B.

“… The Gaussian Mixture model is used to create the partition matrix of the fuzzy c-regression clustering algorithm …”
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Interval type-2 modified fuzzy c-regression model clustering algorithm in TS Fuzzy Model identification von 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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Block Sparse Representations in Modified Fuzzy C-Regression Model Clustering Algorithm for TS Fuzzy Model Identification von 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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Takagi-Sugeno fuzzy model parameters identification based on fuzzy c-regression model clustering algorithm and particle swarm optimization von Soltani, Moez, Chaari, Abdelkader, Ben Hmida, Faycal

“… This new approach combines the advantages of fuzzy c-regression model clustering algorithm and particle swarm optimization …”
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Intuitionistic fuzzy C-regression by using least squares support vector regression von Lin, Kuo-Ping, Chang, Hao-Feng, Chen, Tung-Lian, Lu, Yu-Ming, Wang, Ching-Hsin

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

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

“… Firstly, an improved fuzzy c regression clustering algorithm is proposed to identify the antecedent parameters of T-S fuzzy model …”
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A modified fuzzy c-regression model clustering algorithm for T-S fuzzy model identification von Soltani, M, Aissaoui, B, Chaari, A, Ben Hmida, Faycal, Gossa, M

“… In this paper, a modified fuzzy c-regression model (FCRM) clustering algorithm for identification of Takagi-Sugeno …”
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Hydraulic turbine governing system identification using T–S fuzzy model optimized by chaotic gravitational search algorithm von Li, Chaoshun, Zhou, Jianzhong, Xiao, Jian, Xiao, Han

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

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

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

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

“… •Improving fuzzy clustering models using bio-inspired algorithms.•Comparing the performance of hybrid fuzzy clustering and bio-inspired algorithms …”
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A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model von Güler Dincer, Nevin

“… This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF …”
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Hybrid robust approach for TSK fuzzy modeling with outliers von Chuang, Chen-Chia, Jeng, Jin-Tsong, Tao, Chin-Wang

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

“… 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 von Leski, Jacek M., Kotas, Marian

“… 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 von Kim, Euntai, Park, Minkee, Ji, Seunghwan, Park, Mignon

“… : 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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