Search Results - fuzzy C‐regression model clustering algorithm
-
1
T–S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm
ISSN: 0952-1976, 1873-6769Published: Elsevier Ltd 01.06.2009Published in Engineering applications of artificial intelligence (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…”
Get full text
Journal Article -
2
A fuzzy C‐regression model algorithm using a new PSO algorithm
ISSN: 0890-6327, 1099-1115Published: Bognor Regis Wiley Subscription Services, Inc 01.01.2018Published in International journal of adaptive control and signal processing (01.01.2018)“…‐output local linear Takagi‐Sugeno fuzzy models using the weighted recursive least squares (WRLS…”
Get full text
Journal Article -
3
A type-2 fuzzy c-regression clustering algorithm for Takagi–Sugeno system identification and its application in the steel industry
ISSN: 0020-0255, 1872-6291Published: Elsevier Inc 15.03.2012Published in Information sciences (15.03.2012)“… The Gaussian Mixture model is used to create the partition matrix of the fuzzy c-regression clustering algorithm…”
Get full text
Journal Article -
4
Interval type-2 modified fuzzy c-regression model clustering algorithm in TS Fuzzy Model identification
Published: IEEE 01.07.2016Published in 2016 IEEE International Conference on Fuzzy Systems (FUZZ-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…”
Get full text
Conference Proceeding -
5
Block Sparse Representations in Modified Fuzzy C-Regression Model Clustering Algorithm for TS Fuzzy Model Identification
ISBN: 1479975605, 9781479975600Published: IEEE 01.12.2015Published in 2015 IEEE Symposium Series on Computational Intelligence (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…”
Get full text
Conference Proceeding -
6
Takagi-Sugeno fuzzy model parameters identification based on fuzzy c-regression model clustering algorithm and particle swarm optimization
ISBN: 9781467307826, 1467307823ISSN: 2158-8473Published: IEEE 01.03.2012Published in 2012 16th IEEE Mediterranean Electrotechnical Conference (01.03.2012)“… This new approach combines the advantages of fuzzy c-regression model clustering algorithm and particle swarm optimization…”
Get full text
Conference Proceeding -
7
Intuitionistic fuzzy C-regression by using least squares support vector regression
ISSN: 0957-4174, 1873-6793Published: Elsevier Ltd 01.12.2016Published in 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…”
Get full text
Journal Article -
8
The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm
ISBN: 9781457706523, 1457706520ISSN: 1062-922XPublished: IEEE 01.10.2011Published in 2011 IEEE International Conference on Systems, Man, and Cybernetics (01.10.2011)“…In this paper, the estimation of the state of charge (SOC) of lithium-ion battery by fuzzy c-regression model (FCRM…”
Get full text
Conference Proceeding -
9
Hysteresis Modeling of Piezoelectric Actuators Based on a T-S Fuzzy Model
ISSN: 2079-9292, 2079-9292Published: Basel MDPI AG 01.09.2022Published in 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…”
Get full text
Journal Article -
10
A modified fuzzy c-regression model clustering algorithm for T-S fuzzy model identification
ISBN: 9781457704130, 1457704137Published: IEEE 01.03.2011Published in 2011 8th International Multi-Conference on Systems, Signals and Devices (01.03.2011)“…In this paper, a modified fuzzy c-regression model (FCRM) clustering algorithm for identification of Takagi-Sugeno…”
Get full text
Conference Proceeding -
11
Hydraulic turbine governing system identification using T–S fuzzy model optimized by chaotic gravitational search algorithm
ISSN: 0952-1976, 1873-6769Published: Elsevier Ltd 01.10.2013Published in Engineering applications of artificial intelligence (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…”
Get full text
Journal Article -
12
An Approach Towards the Design of Interval Type-3 T-S Fuzzy System
ISSN: 1063-6706, 1941-0034Published: New York IEEE 01.09.2022Published in 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…”
Get full text
Journal Article -
13
A study of cluster validity criteria for the fuzzy c-regression models clustering algorithm
ISBN: 142440990X, 9781424409907ISSN: 1062-922XPublished: IEEE 01.10.2007Published in 2007 IEEE International Conference on Systems, Man and Cybernetics (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…”
Get full text
Conference Proceeding -
14
Adaptive Inverse Controller Design Based on the Fuzzy C-Regression Model (FCRM) and Back Propagation (BP) Algorithm
ISSN: 2078-2489, 2078-2489Published: Basel MDPI AG 01.12.2019Published in 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…”
Get full text
Journal Article -
15
Characterization and prediction of the backscattered form function of an immersed cylindrical shell using hybrid fuzzy clustering and bio-inspired algorithms
ISSN: 0041-624X, 1874-9968, 1874-9968Published: Netherlands Elsevier B.V 01.02.2018Published in Ultrasonics (01.02.2018)“…•Improving fuzzy clustering models using bio-inspired algorithms.•Comparing the performance of hybrid fuzzy clustering and bio-inspired algorithms…”
Get full text
Journal Article -
16
A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model
ISSN: 1562-2479, 2199-3211Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2018Published in International journal of fuzzy systems (01.08.2018)“…This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF…”
Get full text
Journal Article -
17
Hybrid robust approach for TSK fuzzy modeling with outliers
ISSN: 0957-4174, 1873-6793Published: Elsevier Ltd 01.07.2009Published in 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…”
Get full text
Journal Article -
18
A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization
ISSN: 1641-876X, 2083-8492, 2083-8492Published: Zielona Góra Versita 01.09.2012Published in International Journal of Applied Mathematics and Computer Science (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…”
Get full text
Journal Article -
19
On robust fuzzy c-regression models
ISSN: 0165-0114, 1872-6801Published: Elsevier B.V 15.11.2015Published in 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…”
Get full text
Journal Article -
20
A new approach to fuzzy modeling
ISSN: 1063-6706Published: IEEE 01.08.1997Published in 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…”
Get full text
Journal Article

