-
2
-
-
80053621517
-
Dynamic output feedback predictive control for nonlinear systems represented by a takagi-sugeno model
-
Oct
-
B. C. Ding, "Dynamic output feedback predictive control for nonlinear systems represented by a Takagi-Sugeno model," IEEE Trans. Fuzzy Syst., vol. 19, no. 5, pp. 831-843, Oct. 201-1.
-
(2011)
IEEE Trans. Fuzzy Syst.
, vol.19
, Issue.5
, pp. 831-843
-
-
Ding, B.C.1
-
3
-
-
80053639817
-
Direct model reference takagi-sugeno fuzzy control of siso nonlinear systems
-
Oct
-
M. A. Khanesar, O. Kaynak, andM. Teshnehlab, "Direct model reference Takagi-Sugeno fuzzy control of SISO nonlinear systems," IEEE Trans. Fuzzy Syst., vol. 19, no. 5, pp. 914-924, Oct. 201-1.
-
(2011)
IEEE Trans. Fuzzy Syst.
, vol.19
, Issue.5
, pp. 914-924
-
-
Khanesar, M.A.1
Kaynak, O.2
Teshnehlab, M.3
-
4
-
-
0029406441
-
Building sugeno-type model using fuzzy discretization and orthogonal parameter estimation techniques
-
Nov
-
L. X.Wang and R. Langari, "Building sugeno-type model using fuzzy discretization and orthogonal parameter estimation techniques," IEEE Trans. Fuzzy Syst., vol. 3, no. 4, pp. 454-458, Nov. 199-5.
-
(1995)
IEEE Trans. Fuzzy Syst.
, vol.3
, Issue.4
, pp. 454-458
-
-
Wang, L.X.1
Langari, R.2
-
5
-
-
0027601884
-
Anfis: Adaptive-network-based fuzzy inference systems
-
May
-
J. S. R. Jang, "ANFIS: Adaptive-network-based fuzzy inference systems," IEEE Trans. Syst., Man Cybern., vol. 23, no. 3, pp. 665-685, May 199-3.
-
(1993)
IEEE Trans. Syst., Man Cybern.
, vol.23
, Issue.3
, pp. 665-685
-
-
Jang, J.S.R.1
-
6
-
-
84941531642
-
A new approach to fuzzy-neural system modeling
-
May
-
Y. Lin and G. A. Cunningham, "A new approach to fuzzy-neural system modeling," IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 190-198, May 199-5.
-
(1995)
IEEE Trans. Fuzzy Syst.
, vol.3
, Issue.2
, pp. 190-198
-
-
Lin, Y.1
Cunningham, G.A.2
-
7
-
-
33947267506
-
Adaptive neuro-fuzzy inference systems based approach to nonlinear noise cancellation for images
-
DOI 10.1016/j.fss.2006.10.028, PII S0165011406004842
-
H. Qin and S. X. Yang, "Adaptive neuro-fuzzy inference systems based approach to nonlinear noise cancelation for images," Fuzzy Sets Syst., vol. 158, pp. 1036-1063, 200-7. (Pubitemid 46428431)
-
(2007)
Fuzzy Sets and Systems
, vol.158
, Issue.10
, pp. 1036-1063
-
-
Qin, H.1
Yang, S.X.2
-
8
-
-
0036530967
-
Denfis: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction
-
Ar
-
N. Kasabov, "DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction," IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 144-153, Apr. 200-2.
-
(2002)
IEEE Trans. Fuzzy Syst.
, vol.10
, Issue.2
, pp. 144-153
-
-
Kasabov, N.1
-
9
-
-
11244351634
-
An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network
-
DOI 10.1016/j.fss.2004.03.001, PII S0165011404000843
-
G. Leng, T. M. McGinnity, and G. Prasad, "An approach for on-line extraction of fuzzy rules using a self-organizing fuzzy neural network," Fuzzy Sets Syst., vol. 150, pp. 211-243, 200-5. (Pubitemid 40056019)
-
(2005)
Fuzzy Sets and Systems
, vol.150
, Issue.2
, pp. 211-243
-
-
Leng, G.1
McGinnity, T.M.2
Prasad, G.3
-
10
-
-
0346781553
-
Ten years of genetic fuzzy systems: Current framework and newtrends
-
200-4
-
O. Cordon, F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena, "Ten years of genetic fuzzy systems: Current framework and newtrends," Fuzzy Sets Syst., vol. 141, no. 1, pp. 5-31, 200-4.
-
Fuzzy Sets Syst
, vol.141
, Issue.1
, pp. 5-31
-
-
Cordon, O.1
Gomide, F.2
Herrera, F.3
Hoffmann, F.4
Magdalena, L.5
-
11
-
-
77955504076
-
An evolving construction scheme for fuzzy systems
-
Aug
-
D. Wang, X. J. Zeng, and J. A. Keane, "An evolving construction scheme for fuzzy systems," IEEE Trans. Fuzzy Syst., vol. 18, no. 4, pp. 755-770, Aug. 201-0.
-
(2010)
IEEE Trans. Fuzzy Syst.
, vol.18
, Issue.4
, pp. 755-770
-
-
Wang, D.1
Zeng, X.J.2
Keane, J.A.3
-
12
-
-
58149502268
-
An evolving fuzzy predictor for industrial applications
-
Dec
-
W. Wang and J. Vrbanek, "An evolving fuzzy predictor for industrial applications," IEEE Trans. Fuzzy Syst., vol. 16, no. 6, pp. 1439-1449, Dec. 200-8.
-
(2008)
IEEE Trans. Fuzzy Syst.
, vol.16
, Issue.6
, pp. 1439-1449
-
-
Wang, W.1
Vrbanek, J.2
-
14
-
-
34250725862
-
Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems
-
DOI 10.1109/FUZZY.2006.1682014, 1682014, 2006 IEEE International Conference on Fuzzy Systems
-
J. Botzheim, E. Lughofer, E. P. Klement, and L. Ḱoczy, T. D. Gedeon, "Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems," in Proc. IEEE Int. Conf. Fuzzy Syst., Vancouver, BC, Canada, 2006, pp. 2263-226-9. (Pubitemid 46949057)
-
(2006)
IEEE International Conference on Fuzzy Systems
, pp. 2263-2269
-
-
Botzheim, J.1
Lughofer, E.2
Klement, E.P.3
Koczy, L.T.4
Gedeon, T.D.5
-
16
-
-
34548604303
-
Comparison of different strategies of utilizing fuzzy clustering in structure identification
-
DOI 10.1016/j.ins.2007.06.030, PII S0020025507003192, Including: Mathematics of Uncertainty
-
K. Kilic, O. Uncu, and I. B. Turksen, "Comparison of different strategies of utilizing fuzzy clustering in structure identification," Inf. Sci., vol. 177, pp. 5153-5162, 200-7. (Pubitemid 47409985)
-
(2007)
Information Sciences
, vol.177
, Issue.23
, pp. 5153-5162
-
-
Kilic, K.1
Uncu, O.2
Turksen, I.B.3
-
17
-
-
14644443622
-
On the use of the weighted fuzzy c-means in fuzzy modeling
-
DOI 10.1016/j.advengsoft.2004.12.001, PII S0965997804002224
-
G. E. Tsekouras, "On the use of the weighted fuzzy c-means in fuzzy modeling," Adv. Eng. Softw., vol. 36, pp. 287-300, 200-5. (Pubitemid 40308989)
-
(2005)
Advances in Engineering Software
, vol.36
, Issue.5
, pp. 287-300
-
-
Tsekouras, G.E.1
-
18
-
-
11244351633
-
A hierarchical fuzzy-clustering approach to fuzzy modeling
-
G. E. Tsekouras, H. Sarimveis, E. Kavakli, and G. Bafas, "A hierarchical fuzzy-clustering approach to fuzzy modeling," Fuzzy Sets Syst., vol. 150, pp. 245-267, 200-5.
-
(2005)
Fuzzy Sets Syst.
, vol.150
, pp. 245-267
-
-
Tsekouras, G.E.1
Sarimveis, H.2
Kavakli, E.3
Bafas, G.4
-
19
-
-
84974755191
-
Generation of fuzzy rules by mountain method
-
R. Yager and D. Filev, "Generation of fuzzy rules by mountain method," J. Intell. Fuzzy Syst., vol 2, pp. 209-219, 199-4.
-
(1994)
J. Intell. Fuzzy Syst.
, vol.2
, pp. 209-219
-
-
Yager, R.1
Filev, D.2
-
20
-
-
0024701488
-
Unsupervised optimal fuzzy clustering
-
Jul
-
I. Gath and A. B. Geva, "Unsupervised optimal fuzzy clustering," IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 7, pp. 773-781, Jul. 198-9.
-
(1989)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.11
, Issue.7
, pp. 773-781
-
-
Gath, I.1
Geva, A.B.2
-
21
-
-
0018057468
-
Fuzzy clustering with a fuzzy covariance matrix
-
Adaptive Processes, San Diego, CA, USA, Jan
-
E. E. Gustafson and W. C. Kessel, "Fuzzy clustering with a fuzzy covariance matrix," in Proc. IEEE Conf. Decision Control Including 17th Symp. Adaptive Processes, San Diego, CA, USA, Jan. 1979, pp. 761-76-6.
-
(1979)
Proc. IEEE Conf. Decision Control Including 17th Symp.
, pp. 761-766
-
-
Gustafson, E.E.1
Kessel, W.C.2
-
22
-
-
35448950018
-
Extensions of vector quantization for incremental clustering
-
DOI 10.1016/j.patcog.2007.07.019, PII S0031320307003354, Feature Generation and Machine Learning for Robust Multimodal Biometrics
-
E. Lughofer, "Extensions of vector quantization for incremental clustering," Pattern Recognit., vol. 41, no. 3, pp. 995-1011, 200-8. (Pubitemid 47632671)
-
(2008)
Pattern Recognition
, vol.41
, Issue.3
, pp. 995-1011
-
-
Lughofer, E.1
-
23
-
-
84974743850
-
Fuzzy model identification based on cluster estimation
-
S. Chiu, "Fuzzy model identification based on cluster estimation," J. Intell. Fuzzy Syst., vol. 2, no. 3, pp. 267-278, 199-4.
-
(1994)
J. Intell. Fuzzy Syst.
, vol.2
, Issue.3
, pp. 267-278
-
-
Chiu, S.1
-
24
-
-
0033078615
-
Simplifying fuzzy rule-based models using orthogonal transformation methods
-
Feb
-
J. Yen and L. Wang, "Simplifying fuzzy rule-based models using orthogonal transformation methods," IEEE Trans. Syst. Man Cybern., vol. 29, no. 1, pp. 13-24, Feb. 199-9.
-
(1999)
IEEE Trans. Syst. Man Cybern.
, vol.29
, Issue.1
, pp. 13-24
-
-
Yen, J.1
Wang, L.2
-
25
-
-
54049155041
-
Total least squares in fuzzy system identification: An application to an industrial engine
-
S. Jakubek, C. Hametner, and N. Keuth, "Total least squares in fuzzy system identification: An application to an industrial engine," Eng. Appl. Artif. Intell., vol. 21, no. 8, pp. 1277-1288, 200-8.
-
(2008)
Eng. Appl. Artif. Intell.
, vol.21
, Issue.8
, pp. 1277-1288
-
-
Jakubek, S.1
Hametner, C.2
Keuth, N.3
-
26
-
-
0026928374
-
Fuzzy basis functions, universal approximation and orthogonal least-squares learning
-
Se
-
L. X. Wang and J. M. Mendel, "Fuzzy basis functions, universal approximation and orthogonal least-squares learning," IEEE Trans. Neural Netw., vol. 3, no. 5, pp. 807-814, Sep. 199-2.
-
(1992)
IEEE Trans. Neural Netw.
, vol.3
, Issue.5
, pp. 807-814
-
-
Wang, L.X.1
Mendel, J.M.2
-
27
-
-
34447298360
-
Building an interpretable fuzzy rule base from data using orthogonal least squares- application to a depollution problem
-
200-7
-
S. Destercke, S. Guillaume, and B. Charnomordic, "Building an interpretable fuzzy rule base from data using orthogonal least squares- application to a depollution problem," Fuzzy Sets Syst., vol. 158, no. 18, pp. 2078-2094, 200-7.
-
Fuzzy Sets Syst
, vol.158
, Issue.18
, pp. 2078-2094
-
-
Destercke, S.1
Guillaume, S.2
Charnomordic, B.3
-
28
-
-
0033115927
-
Reduction of fuzzy rule base via singular value decomposition
-
Ar
-
Y. Yam, P. Baranyi, and C. T. Yang, "Reduction of fuzzy rule base via singular value decomposition," IEEE Trans. Fuzzy Syst., vol. 7, no. 2, pp. 120-131, Apr. 199-9.
-
(1999)
IEEE Trans. Fuzzy Syst.
, vol.7
, Issue.2
, pp. 120-131
-
-
Yam, Y.1
Baranyi, P.2
Yang, C.T.3
-
29
-
-
0037318663
-
Svd based reduction tomiso ts fuzzy models
-
Feb
-
P. Baranyi, Y. Yam, A. V́arkonyi-Ḱoczy, and R. J. Patton, "SVD based reduction toMISO TS fuzzy models," IEEE Trans. Ind. Electron., vol. 50. no. 1, pp. 232-242, Feb. 200-3.
-
(2003)
IEEE Trans. Ind. Electron.
, vol.50
, Issue.1
, pp. 232-242
-
-
Baranyi, P.1
Yam, Y.2
V́arkonyi-Ḱoczy, A.3
Patton, R.J.4
-
30
-
-
1942423639
-
Tp model transformation as a way to lmi based controller design
-
Ar
-
P. Baranyi, "TP model transformation as a way to LMI based controller design," IEEE Trans. Ind. Electron., vol. 51, no. 2, pp. 387-400, Apr. 200-4.
-
(2004)
IEEE Trans. Ind. Electron.
, vol.51
, Issue.2
, pp. 387-400
-
-
Baranyi, P.1
-
31
-
-
33744797404
-
Case study of the TP-model transformation in the control of a complex dynamic model with structural nonlinearity
-
DOI 10.1109/TIE.2006.874265
-
P. Baranyi and Y. Yam, "Case study of the TP model transformation in the control design of a complex dynamic model with structural non-linearity," IEEE Trans. Ind. Electron., vol. 53. no. 3, pp. 895-904, Jun. 200-6. (Pubitemid 43834609)
-
(2006)
IEEE Transactions on Industrial Electronics
, vol.53
, Issue.3
, pp. 895-904
-
-
Baranyi, P.1
Yam, Y.2
-
32
-
-
0042700003
-
From differential equations to pdc controller design via numerical transformation
-
P. Baranyi, D. Tikk, Y. Yam, and R. J. Patton, "From differential equations to PDC controller design via numerical transformation," Comput. Ind., vol. 51, pp. 281-297, 200-3.
-
(2003)
Comput. Ind.
, vol.51
, pp. 281-297
-
-
Baranyi, P.1
Tikk, D.2
Yam, Y.3
Patton, R.J.4
-
33
-
-
35549007294
-
Approximation properties of TP model forms and its consequences to TPDC design framework
-
D. Tikk, P. Baranyi, and R. J. Patton, "Approximation properties of TP model forms and its consequents to TPDC design framework," Asian J. Contr., vol. 9, no. 3, pp. 221-231, 200-7. (Pubitemid 350010477)
-
(2007)
Asian Journal of Control
, vol.9
, Issue.3
, pp. 221-231
-
-
Tikk, D.1
Baranyi, P.2
Patton, R.J.3
-
34
-
-
0034476279
-
Representing membership functions as points in high-dimensional spaces for fuzzy interpolation and extrapolation
-
DOI 10.1109/91.890335
-
Y. Yamand L. T. Ḱoczy, "Representingmembership functions as points in high-dimensional spaces for fuzzy interpolation and extrapolation," IEEE Trans. Fuzzy Syst., vol. 8, no. 6, pp. 761-772, Dec. 200-0. (Pubitemid 32130577)
-
(2000)
IEEE Transactions on Fuzzy Systems
, vol.8
, Issue.6
, pp. 761-772
-
-
Yam, Y.1
Koczy, L.T.2
-
35
-
-
30344465742
-
Fuzzy rule interpolation for multidimensional input spaces with applications: A case study
-
DOI 10.1109/TFUZZ.2005.859316
-
K. W.Wong, D. Tikk, T. D. Gedeon, and L. T. Ḱoczy, "Rule interpolation for multidimensional input spaces with applications: A case study," IEEE Trans. Fuzzy Syst., vol. 13, no. 6, pp. 809-819, Dec. 200-5. (Pubitemid 43065964)
-
(2005)
IEEE Transactions on Fuzzy Systems
, vol.13
, Issue.6
, pp. 809-819
-
-
Wong, K.W.1
Tikk, D.2
Gedeon, T.D.3
Koczy, L.T.4
-
36
-
-
10944265590
-
Rule interpolation by α-level sets in fuzzy approximate reasoning
-
L. T. Ḱoczy, K. Hirota, "Rule interpolation by α-level sets in fuzzy approximate reasoning," Bulletin Stud. Exchanges Fuzz. Appl., vol. 46, pp. 115-123, 199-1.
-
(1991)
Bulletin Stud. Exchanges Fuzz. Appl.
, vol.46
, pp. 115-123
-
-
Ḱoczy, L.T.1
Hirota, K.2
-
37
-
-
10944267254
-
A generalized concept for fuzzy rule interpolation
-
Dec
-
P. Baranyi, L. T. Ḱoczy, and T. D. Gedeon, "A generalized concept for fuzzy rule interpolation," IEEE Trans. Fuzzy Syst., vol. 12, no. 6, pp. 820- 832, Dec. 200-4.
-
(2004)
IEEE Trans. Fuzzy Syst.
, vol.12
, Issue.6
, pp. 820-832
-
-
Baranyi, P.1
Ḱoczy, L.T.2
Gedeon, T.D.3
-
38
-
-
0034204783
-
Comprehensive analysis of a new fuzzy rule interpolation method
-
Jun
-
D. Tikk and P. Baranyi, "Comprehensive analysis of a new fuzzy rule interpolation method," IEEE Trans. Fuzzy Syst., vol. 8, no. 3, pp. 281- 296, Jun. 200-0.
-
(2000)
IEEE Trans. Fuzzy Syst.
, vol.8
, Issue.3
, pp. 281-296
-
-
Tikk, D.1
Baranyi, P.2
-
39
-
-
77649256868
-
Hosvd based canonical form for polytopic models of dynamic systems
-
L. Szeidl and P. V́arlaki, "HOSVD based canonical form for polytopic models of dynamic systems," J. Adv. Comput. Intell. Inf., vol. 13, no. 1, pp. 52-60, 200-9.
-
(2009)
J. Adv. Comput. Intell. Inf.
, vol.13
, Issue.1
, pp. 52-60
-
-
Szeidl, L.1
V́arlaki, P.2
-
40
-
-
77950638805
-
Sparsefis: Data-driven learning of fuzzy systems with sparsity constraints
-
Ar
-
E. Lughofer and S. Kindermann, "SparseFIS: Data-driven learning of fuzzy systems with sparsity constraints," IEEE Trans. Fuzzy Syst., vol. 18, no. 2, pp. 396-411, Apr. 201-0.
-
(2010)
IEEE Trans. Fuzzy Syst.
, vol.18
, Issue.2
, pp. 396-411
-
-
Lughofer, E.1
Kindermann, S.2
-
41
-
-
33645035051
-
Model selection and estimation in regression with grouped variables
-
DOI 10.1111/j.1467-9868.2005.00532.x
-
M. Yuan and Y. Lin, "Model selection and estimation in regression with grouped variables," J. Roy. Statist. Soc. B, vol. 68, no. 1, pp. 49-67, 200-6. (Pubitemid 43415335)
-
(2006)
Journal of the Royal Statistical Society. Series B: Statistical Methodology
, vol.68
, Issue.1
, pp. 49-67
-
-
Yuan, M.1
Lin, Y.2
-
42
-
-
80051715867
-
Grouped orthogonal matching pursuit for variable selection and prediction
-
A. C. Lozano and G. Swirszcz, N. Abe, "Grouped orthogonal matching pursuit for variable selection and prediction," in Proc. Neural Inform. Process. Syst., 200-9.
-
(2009)
Proc. Neural Inform. Process. Syst.
-
-
Lozano, A.C.1
Swirszcz, G.2
-
43
-
-
77958006903
-
Fast group sparse classification
-
M. Angshul and K. Rabab, "Fast group sparse classification," Can. J. Electr. Comput. Eng., vol. 34, no. 4, pp. 136-144, 200-9.
-
(2009)
Can. J. Electr. Comput. Eng.
, vol.34
, Issue.4
, pp. 136-144
-
-
Angshul, M.1
Rabab, K.2
-
44
-
-
84871694297
-
Structured sparse representation appearance model for robust visual tracking
-
May
-
T. X. Bai, Y. F. Li, and Y. Z Tang, "Structured sparse representation appearance model for robust visual tracking," in Proc. Int. Conf. Robot. Autom., May 2011, pp. 4399-440-4.
-
(2011)
Proc. Int. Conf. Robot. Autom.
, pp. 4399-4404
-
-
Bai, T.X.1
Li, Y.F.2
Tang, Y.Z.3
-
46
-
-
64649083745
-
Signal recovery from random measurements via orthogonal matching pursuit
-
Dec
-
J. A. Tropp and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Trans. Inf. Theor., vol. 53, no. 12, pp. 4655-4666, Dec. 200-7.
-
(2007)
IEEE Trans. Inf. Theor.
, vol.53
, Issue.12
, pp. 4655-4666
-
-
Tropp, J.A.1
Gilbert, A.C.2
-
47
-
-
64149088421
-
On the consistency of feature selection using greedy least squares regression
-
T. Zhang, "On the consistency of feature selection using greedy least squares regression," J. Mach. Learn. Res., vol. 10, pp. 555-568, 200-9.
-
(2009)
J. Mach. Learn. Res.
, vol.10
, pp. 555-568
-
-
Zhang, T.1
-
48
-
-
0032205732
-
Improving the interpretability of TSK fuzzy models by combining global learning and local learning
-
PII S1063670698082629
-
J. Yen, L. Wang, and C. W. Gillespie, "Improving the interpretability of TSK fuzzy models by combining global learning and local learning," IEEE Trans. Fuzzy Syst., vol. 6, no. 4, pp. 530-537, Nov. 199-8. (Pubitemid 128750083)
-
(1998)
IEEE Transactions on Fuzzy Systems
, vol.6
, Issue.4
, pp. 530-537
-
-
Yen, J.1
Wang, L.2
Gillespie, C.W.3
-
50
-
-
84890520049
-
Use of the zero normwith linear models and kernel methods
-
J.Weston, A. Elisseeff, andB. Scholkopf, "Use of the zero normwith linear models and kernel methods," J. Mach. Learn. Res., vol. 3, pp. 1439-1461, 200-3.
-
(2003)
J. Mach. Learn. Res.
, vol.3
, pp. 1439-1461
-
-
Weston, J.1
Elisseeff, A.2
Scholkopf, B.3
-
51
-
-
0001287271
-
Regression shrinkage and selection via the lasso
-
R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Roy. Statist. Soc. B, vol. 58, pp. 267-288, 199-6.
-
(1996)
J. Roy. Statist. Soc. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
52
-
-
84950445313
-
Cross-validation of regression models
-
R. Picard and D. Cook, "Cross-validation of regression models," J. Amer. Statist. Assoc., vol. 79, no. 387, pp. 575-583, 198-4.
-
(1984)
J. Amer. Statist. Assoc.
, vol.79
, Issue.387
, pp. 575-583
-
-
Picard, R.1
Cook, D.2
-
53
-
-
85164392958
-
A study of cross-validation and bootstrap for accuracy estimation and model selection
-
R. Kohavi, "A study of cross-validation and bootstrap for accuracy estimation and model selection," in Proc. 14th Int. Joint Conf. Artif. Intell., 1995, vol. 2, no. 12, pp. 1137-114-5.
-
(1995)
Proc. 14th Int. Joint Conf. Artif. Intell.
, vol.2
, Issue.12
, pp. 1137-1145
-
-
Kohavi, R.1
-
54
-
-
0032164985
-
A simply identified Sugeno-type fuzzy model via double clustering
-
PII S0020025597100834
-
E. Kim, H. Lee, and M. Park, "A simply identified Sugeno-type fuzzy model via double clustering," Inf. Sci. vol. 110, no. 1/2, pp. 25-39, 199-8. (Pubitemid 128369951)
-
(1998)
Information Sciences
, vol.110
, Issue.1-2
, pp. 25-39
-
-
Kim, E.1
Lee, H.2
Park, M.3
Park, M.4
-
55
-
-
0034300570
-
Identification of fuzzy systems by means of an auto-tuning algorithm and its application to nonlinear systems
-
S. K. Oh and W. Pedrycz, "Identification of fuzzy systems by means of an auto-tuning algorithm and its application to nonlinear systems," Fuzzy Sets Syst., vol. 115, no. 2, pp. 205-230, 200-0.
-
(2000)
Fuzzy Sets Syst.
, vol.115
, Issue.2
, pp. 205-230
-
-
Oh, S.K.1
Pedrycz, W.2
-
56
-
-
84863251575
-
Identification of fuzzy inference systems using a multi-objective space search algorithm and information granulation
-
W. Huang, S. K. Oh, L. Ding, H. K. Kim, and S. C. Joo, "Identification of fuzzy inference systems using a multi-objective space search algorithm and information granulation," J. Electr. Eng., vol. 6, no. 6, pp. 853-866, 201-1.
-
(2011)
J. Electr. Eng.
, vol.6
, Issue.6
, pp. 853-866
-
-
Huang, W.1
Oh, S.K.2
Ding, L.3
Kim, H.K.4
Joo, S.C.5
-
57
-
-
50149097761
-
Identification of fuzzy models using a successive tuning method with a variant identification ratio
-
J. Choi, S. K. Oh, and W. Pedrycz, "Identification of fuzzy models using a successive tuning method with a variant identification ratio," Fuzzy Sets Syst., vol. 159, no. 21, pp. 2873-2889, 200-8.
-
(2008)
Fuzzy Sets Syst.
, vol.159
, Issue.21
, pp. 2873-2889
-
-
Choi, J.1
Oh, S.K.2
Pedrycz, W.3
-
58
-
-
70350605478
-
Data-driven fuzzy modeling for takagi-sugeno-kang fuzzy system
-
B. Rezaee and M. H. Fazel Zarandi, "Data-driven fuzzy modeling for takagi-sugeno-kang fuzzy system," Inf. Sci. vol. 180, pp. 241-255, 201-0.
-
(2010)
Inf. Sci.
, vol.180
, pp. 241-255
-
-
Rezaee, B.1
Fazel Zarandi, M.H.2
-
59
-
-
84859722569
-
T-s fuzzy model identification with gravitational search based hyper-plane clustering algorithm
-
Ar
-
C. S. Li, J. Z. Zhou, B. Fu, P. Kou, and J. Xiao, "T-S fuzzy model identification with gravitational search based hyper-plane clustering algorithm," IEEE Trans. Fuzzy Syst., vol. 20, no. 2, pp. 305-317, Apr. 201-2.
-
(2012)
IEEE Trans. Fuzzy Syst.
, vol.20
, Issue.2
, pp. 305-317
-
-
Li, C.S.1
Zhou, J.Z.2
Fu, B.3
Kou, P.4
Xiao, J.5
-
60
-
-
0036791593
-
Modified gath-geva fuzzy clustering for identification of takagi-sugeno fuzzy models
-
Oct
-
J. Abonyi and R. Babusska, F. Szeifert, "Modified gath-geva fuzzy clustering for identification of takagi-sugeno fuzzy models," IEEE Trans. Syst. Man Cybern., vol. 32, no. 5, pp. 612-621, Oct. 200-2.
-
(2002)
IEEE Trans. Syst. Man Cybern.
, vol.32
, Issue.5
, pp. 612-621
-
-
Abonyi, J.1
Babusska, R.2
Szeifert, F.3
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