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Volumn 24, Issue 2, 2013, Pages 219-230

Radial basis function network training using a nonsymmetric partition of the input space and particle swarm optimization

Author keywords

Fuzzy means algorithm; Fuzzy partition; Nonsymmetric partition; Particle swarm optimization; Radial basis function

Indexed keywords

FUZZY MEANS; FUZZY PARTITION; INTEGRATED FRAMEWORKS; NEURAL NETWORK TRAINING; NONSYMMETRIC; PREDICTION ACCURACY; RADIAL BASIS FUNCTIONS; SYNTHETIC BENCHMARK;

EID: 84875522416     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2012.2227794     Document Type: Article
Times cited : (114)

References (54)
  • 1
    • 34250122797 scopus 로고
    • Interpolation of scattered data: Distance matrices and conditionally positive definite functions
    • Mar.
    • C. A. Michelli, "Interpolation of scattered data: Distance matrices and conditionally positive definite functions," Constr. Approx., vol. 2, pp. 11-22, Mar. 1986.
    • (1986) Constr. Approx. , vol.2 , pp. 11-22
    • Michelli, C.A.1
  • 2
    • 0025490985 scopus 로고
    • Networks for approximation and learning
    • Sep.
    • T. Poggio and F. Girosi, "Networks for approximation and learning," Proc. IEEE, vol. 78, no. 9, pp. 1481-1497, Sep. 1990.
    • (1990) Proc. IEEE , vol.78 , Issue.9 , pp. 1481-1497
    • Poggio, T.1    Girosi, F.2
  • 3
    • 0000672424 scopus 로고
    • Fast learning in networks of locally-tuned processing units
    • J. Moody and C. Darken, "Fast learning in networks of locally-tuned processing units," Neural Comput., vol. 1, no. 2, pp. 281-294, 1989.
    • (1989) Neural Comput. , vol.1 , Issue.2 , pp. 281-294
    • Moody, J.1    Darken, C.2
  • 4
    • 0025554567 scopus 로고
    • Fast adaptive K-means clustering: Some empirical results
    • San Diego, CA Mar.
    • C. Darken and J. Moody, "Fast adaptive K-means clustering: Some empirical results," in Proc. IEEE Int. Joint Conf. Neural Netw., San Diego, CA, Mar. 1990, pp. 233-238.
    • (1990) Proc. IEEE Int. Joint Conf. Neural Netw. , pp. 233-238
    • Darken, C.1    Moody, J.2
  • 5
    • 0026116468 scopus 로고
    • Orthogonal least squares learning algorithm for radial basis function networks
    • Mar.
    • S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis function networks," IEEE Trans. Neural Netw., vol. 2, no. 2, pp. 302-309, Mar. 1991.
    • (1991) IEEE Trans. Neural Netw. , vol.2 , Issue.2 , pp. 302-309
    • Chen, S.1    Cowan, C.F.N.2    Grant, P.M.3
  • 6
    • 33746862896 scopus 로고    scopus 로고
    • A fast identification algorithm for box-cox transformation based radial basis function neural network
    • Jul.
    • X. Hong, "A fast identification algorithm for box-cox transformation based radial basis function neural network," IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 1064-1069, Jul. 2006.
    • (2006) IEEE Trans. Neural Netw. , vol.17 , Issue.4 , pp. 1064-1069
    • Hong, X.1
  • 7
    • 64049119709 scopus 로고    scopus 로고
    • Construction of tunable radial basis function networks using orthogonal forward selection
    • Apr.
    • S. Chen, X. Hong, B. L. Luk, and C. J. Harris, "Construction of tunable radial basis function networks using orthogonal forward selection," IEEE Trans. Syst., Man., Cybern. B, Cybern., vol. 39, no. 2, pp. 457-466, Apr. 2009.
    • (2009) IEEE Trans. Syst., Man., Cybern. B, Cybern. , vol.39 , Issue.2 , pp. 457-466
    • Chen, S.1    Hong, X.2    Luk, B.L.3    Harris, C.J.4
  • 8
    • 33846063532 scopus 로고    scopus 로고
    • Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure
    • Nov.
    • S. Chen, X. X. Wang, X. Hong, and C. J. Harris, "Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure," IEEE Trans. Neural Netw., vol. 17, no. 6, pp. 1652-1656, Nov. 2006.
    • (2006) IEEE Trans. Neural Netw. , vol.17 , Issue.6 , pp. 1652-1656
    • Chen, S.1    Wang, X.X.2    Hong, X.3    Harris, C.J.4
  • 9
    • 79960699968 scopus 로고    scopus 로고
    • Radial basis function neural network with incremental learning for face recognition
    • Aug.
    • Y. W. Wong, K. P. Seng, and L. M. Ang, "Radial basis function neural network with incremental learning for face recognition," IEEE Trans. Syst., Man., Cybern. B, Cybern., vol. 41, no. 4, pp. 940-949, Aug. 2011.
    • (2011) IEEE Trans. Syst., Man., Cybern. B, Cybern. , vol.41 , Issue.4 , pp. 940-949
    • Wong, Y.W.1    Seng, K.P.2    Ang, L.M.3
  • 10
    • 77956340081 scopus 로고    scopus 로고
    • Constructive approximation to multivariate function by decay RBF neural network
    • Sep.
    • M. Hou and X. Han, "Constructive approximation to multivariate function by decay RBF neural network," IEEE Trans. Neural Netw., vol. 21, no. 9, pp. 1517-1523, Sep. 2010.
    • (2010) IEEE Trans. Neural Netw. , vol.21 , Issue.9 , pp. 1517-1523
    • Hou, M.1    Han, X.2
  • 11
    • 0031568361 scopus 로고    scopus 로고
    • A sequential learning scheme for function approximation using minimal radial basis function neural networks
    • L. Yingwei, N. Sundararajan, and P. Saratchandran, "A sequential learning scheme for function approximation using minimal radial basis function neural networks," Neural Comput., vol. 19, no. 2, pp. 461-478, 1997.
    • (1997) Neural Comput. , vol.19 , Issue.2 , pp. 461-478
    • Yingwei, L.1    Sundararajan, N.2    Saratchandran, P.3
  • 12
    • 0032123243 scopus 로고    scopus 로고
    • An efficient MDL-based construction of RBF networks
    • A. Leonardis and H. Bischof, "An efficient MDL-based construction of RBF networks," Neural Netw., vol. 11, no. 5, pp. 963-973, 1998.
    • (1998) Neural Netw. , vol.11 , Issue.5 , pp. 963-973
    • Leonardis, A.1    Bischof, H.2
  • 13
    • 0037138659 scopus 로고    scopus 로고
    • A fast and efficient algorithm for training radial basis function neural networks based on a fuzzy partition of the input space
    • H. Sarimveis, A. Alexandridis, G. Tsekouras, and G. Bafas, "A fast and efficient algorithm for training radial basis function neural networks based on a fuzzy partition of the input space," Ind. Eng. Chem. Res., vol. 41, no. 4, pp. 751-759, 2002.
    • (2002) Ind. Eng. Chem. Res. , vol.41 , Issue.4 , pp. 751-759
    • Sarimveis, H.1    Alexandridis, A.2    Tsekouras, G.3    Bafas, G.4
  • 14
    • 77950804457 scopus 로고    scopus 로고
    • Fuzzy clustering with viewpoints
    • Apr.
    • W Pedrycz, V. Loia, and S. Senatore, "Fuzzy clustering with viewpoints," IEEE Trans. Fuzzy Syst., vol. 18, no. 2, pp. 274-284, Apr. 2010.
    • (2010) IEEE Trans. Fuzzy Syst. , vol.18 , Issue.2 , pp. 274-284
    • Pedrycz, W.1    Loia, V.2    Senatore, S.3
  • 15
    • 77953706322 scopus 로고    scopus 로고
    • Integrating clustering and supervised learning for categorical data analysis
    • Jul.
    • U. Maulik, S. Bandyopadhyay, and I. Saha, "Integrating clustering and supervised learning for categorical data analysis," IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, vol. 40, no. 4, pp. 664-675, Jul. 2010.
    • (2010) IEEE Trans. Syst., Man, Cybern. A, Syst. Humans , vol.40 , Issue.4 , pp. 664-675
    • Maulik, U.1    Bandyopadhyay, S.2    Saha, I.3
  • 16
    • 77957777625 scopus 로고    scopus 로고
    • Spatially constrained fuzzy-clustering-based sensor placement for spatiotemporal fuzzy-control system
    • Oct.
    • X. X. Zhang, H. X. Li, and C. K. Qi, "Spatially constrained fuzzy-clustering-based sensor placement for spatiotemporal fuzzy-control system," IEEE Trans. Fuzzy Syst., vol. 18, no. 5, pp. 946-957, Oct. 2010.
    • (2010) IEEE Trans. Fuzzy Syst. , vol.18 , Issue.5 , pp. 946-957
    • Zhang, X.X.1    Li, H.X.2    Qi, C.K.3
  • 17
    • 0742290061 scopus 로고    scopus 로고
    • A new algorithm for online structure and parameter adaptation of RBF networks
    • A. Alexandridis, H. Sarimveis, and G. Bafas, "A new algorithm for online structure and parameter adaptation of RBF networks," Neural Netw., vol. 16, no. 7, pp. 1003-1017, 2003.
    • (2003) Neural Netw. , vol.16 , Issue.7 , pp. 1003-1017
    • Alexandridis, A.1    Sarimveis, H.2    Bafas, G.3
  • 18
    • 79960840823 scopus 로고    scopus 로고
    • A radial basis function network training algorithm using a non-symmetric partition of the input space - application to a model predictive control configuration
    • A. Alexandridis, H. Sarimveis, and K. Ninos, "A radial basis function network training algorithm using a non-symmetric partition of the input space - application to a model predictive control configuration," Adv. Eng. Softw., vol. 42, no. 10, pp. 830-837, 2011.
    • (2011) Adv. Eng. Softw. , vol.42 , Issue.10 , pp. 830-837
    • Alexandridis, A.1    Sarimveis, H.2    Ninos, K.3
  • 19
    • 0026135904 scopus 로고
    • Radial basis function networks for classifying process faults
    • Apr.
    • J. A. Leonard and M. A. Kramer, "Radial basis function networks for classifying process faults," IEEE Control Syst., vol. 11, no. 3, pp. 31-38, Apr. 1991.
    • (1991) IEEE Control Syst. , vol.11 , Issue.3 , pp. 31-38
    • Leonard, J.A.1    Kramer, M.A.2
  • 20
    • 85042234389 scopus 로고    scopus 로고
    • Optimising the widths of radial basis functions
    • M. Orr, "Optimising the widths of radial basis functions," in Proc. 5th Brazilian Symp. Neural Netw., 1998, pp. 26-29.
    • (1998) Proc. 5th Brazilian Symp. Neural Netw. , pp. 26-29
    • Orr, M.1
  • 21
    • 79959507049 scopus 로고    scopus 로고
    • Euclidean distance and second derivative based widths optimization of radial basis function neural networks
    • Barcelona, Spain
    • W Yao, X. Chen, M. V. Tooren, and Y Wei, "Euclidean distance and second derivative based widths optimization of radial basis function neural networks," in Proc. Int. Joint Conf. Neural Netw., Barcelona, Spain, 2010, pp. 1-8.
    • (2010) Proc. Int. Joint Conf. Neural Netw. , pp. 1-8
    • Yao, W.1    Chen, X.2    Tooren, M.V.3    Wei, Y.4
  • 22
    • 84875152882 scopus 로고    scopus 로고
    • Concurrent subspace width optimization method for RBF neural network modeling
    • Feb.
    • W Yao, X. Chen, Y Zhao, and M. V. Tooren, "Concurrent subspace width optimization method for RBF neural network modeling," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 2, pp. 247-259, Feb. 2012.
    • (2012) IEEE Trans. Neural Netw. Learn. Syst. , vol.23 , Issue.2 , pp. 247-259
    • Yao, W.1    Chen, X.2    Zhao, Y.3    Tooren, M.V.4
  • 23
    • 84856270947 scopus 로고    scopus 로고
    • Radial basis function networks with linear interval regression weights for symbolic interval data
    • Feb.
    • S. F. Su, C. C. Chuang, C. W. Tao, J. J. Jeng, and C. C. Hsiao, "Radial basis function networks with linear interval regression weights for symbolic interval data," IEEE Trans. Syst., Man., Cybern. B, Cybern., vol. 42, no. 1, pp. 69-80, Feb. 2012.
    • (2012) IEEE Trans. Syst., Man., Cybern. B, Cybern. , vol.42 , Issue.1 , pp. 69-80
    • Su, S.F.1    Chuang, C.C.2    Tao, C.W.3    Jeng, J.J.4    Hsiao, C.C.5
  • 24
    • 30344476977 scopus 로고    scopus 로고
    • Fuzzy nonlinear regression with fuzzified radial basis function network
    • Dec.
    • D. Zhang, L.F. Deng, K. Y Cai, and A. So, "Fuzzy nonlinear regression with fuzzified radial basis function network," IEEE Trans. Fuzzy Syst., vol. 13, no. 6, pp. 742-760, Dec. 2005.
    • (2005) IEEE Trans. Fuzzy Syst. , vol.13 , Issue.6 , pp. 742-760
    • Zhang, D.1    Deng, L.F.2    Cai, K.Y.3    So, A.4
  • 25
    • 0031238274 scopus 로고    scopus 로고
    • Radial basis function networks, regression weights, and the expectation-maximization algorithm
    • Sep.
    • R. Langari, L. Wang, and J. Yen, "Radial basis function networks, regression weights, and the expectation-maximization algorithm," IEEE Trans. Syst., Man., Cybern. A, Syst. Humans, vol. 27, no. 5, pp. 613-623, Sep. 1997.
    • (1997) IEEE Trans. Syst., Man., Cybern. A, Syst. Humans , vol.27 , Issue.5 , pp. 613-623
    • Langari, R.1    Wang, L.2    Yen, J.3
  • 26
    • 0000211514 scopus 로고    scopus 로고
    • Robust full Bayesian learning for radial basis networks
    • C. Andrieu, N. D. Freitas, and A. Doucet, "Robust full Bayesian learning for radial basis networks," Neural Comput., vol. 13, no. 10, pp. 2359-2407, 2001.
    • (2001) Neural Comput. , vol.13 , Issue.10 , pp. 2359-2407
    • Andrieu, C.1    Freitas, N.D.2    Doucet, A.3
  • 27
    • 79957991143 scopus 로고    scopus 로고
    • Efficient algorithm for training interpolation RBF networks with equally spaced nodes
    • Jun.
    • H. X. Huan, D. T. T. Hien, and H. H. Tue, "Efficient algorithm for training interpolation RBF networks with equally spaced nodes," IEEE Trans. Neural Netw., vol. 22, no. 6, pp. 982-988, Jun. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.6 , pp. 982-988
    • Huan, H.X.1    Hien, D.T.T.2    Tue, H.H.3
  • 28
    • 84876921583 scopus 로고    scopus 로고
    • Fast and efficient second-order method for training radial basis function networks
    • Apr.
    • T. Xie, H. Yu, J. Hewlett, P. Rózycki, and B. Wilamowski, "Fast and efficient second-order method for training radial basis function networks," IEEE Trans. Neural Netw., vol. 23, no. 4, pp. 609-619, Apr. 2012.
    • (2012) IEEE Trans. Neural Netw. , vol.23 , Issue.4 , pp. 609-619
    • Xie, T.1    Yu, H.2    Hewlett, J.3    Rózycki, P.4    Wilamowski, B.5
  • 29
    • 0346099405 scopus 로고    scopus 로고
    • A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms
    • H. Sarimveis, A. Alexandridis, S. Mazarakis, and G. Bafas, "A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms," Comput. Chem. Eng., vol. 28, nos. 1-2, pp. 209-217, 2004.
    • (2004) Comput. Chem. Eng. , vol.28 , Issue.1-2 , pp. 209-217
    • Sarimveis, H.1    Alexandridis, A.2    Mazarakis, S.3    Bafas, G.4
  • 30
    • 79951675527 scopus 로고    scopus 로고
    • Logistic regression by means of evolutionary radial basis function neural networks
    • Feb.
    • P. A. Gutiérrez, C. Hervás-Martínez, and F. J. Martínez-Estudillo, "Logistic regression by means of evolutionary radial basis function neural networks," IEEE Trans. Neural Netw., vol. 22, no. 2, pp. 246-263, Feb. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.2 , pp. 246-263
    • Gutiérrez, P.A.1    Hervás-Martínez, C.2    Martínez-Estudillo, F.J.3
  • 31
    • 0742321288 scopus 로고    scopus 로고
    • Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation
    • Nov.
    • J. González, I. Rojas, J. Ortega, H. Pomares, F. J. Fernández, and A. F. Díaz, "Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation," IEEE Trans. Neural Netw., vol. 14, no. 6, pp. 1478-1495, Nov. 2003.
    • (2003) IEEE Trans. Neural Netw. , vol.14 , Issue.6 , pp. 1478-1495
    • González, J.1    Rojas, I.2    Ortega, J.3    Pomares, H.4    Fernández, F.J.5    Díaz, A.F.6
  • 32
    • 26844578765 scopus 로고    scopus 로고
    • Evolutionary optimization of radial basis function classifiers for data mining applications
    • Oct.
    • O. Buchtala, M. Klimek, and B. Sick, "Evolutionary optimization of radial basis function classifiers for data mining applications," IEEE Trans. Syst., Man., Cybern. B, Cybern., vol. 35, no. 5, pp. 928-947, Oct. 2005.
    • (2005) IEEE Trans. Syst., Man., Cybern. B, Cybern. , vol.35 , Issue.5 , pp. 928-947
    • Buchtala, O.1    Klimek, M.2    Sick, B.3
  • 33
    • 84879592882 scopus 로고    scopus 로고
    • Evolutionary method combining particle swarm optimisation and genetic algorithms using fuzzy logic for parameter adaptation and aggregation: The case neural network optimisation for face recognition
    • F. Valdez, P. Melin, and O. Castillo, "Evolutionary method combining particle swarm optimisation and genetic algorithms using fuzzy logic for parameter adaptation and aggregation: The case neural network optimisation for face recognition," Int. J. Artif. Intell. Soft Comput., vol. 2, nos. 1-2, pp. 77-102, 2010.
    • (2010) Int. J. Artif. Intell. Soft Comput. , vol.2 , Issue.1-2 , pp. 77-102
    • Valdez, F.1    Melin, P.2    Castillo, O.3
  • 34
    • 78751621343 scopus 로고    scopus 로고
    • An improved evolutionary method with fuzzy logic for combining particle swarm optimization and genetic algorithms
    • F. Valdez, P. Melin, and O. Castillo, "An improved evolutionary method with fuzzy logic for combining particle swarm optimization and genetic algorithms," Appl. Soft Comput., vol. 11, no. 2, pp. 2625-2632, 2011.
    • (2011) Appl. Soft Comput. , vol.11 , Issue.2 , pp. 2625-2632
    • Valdez, F.1    Melin, P.2    Castillo, O.3
  • 35
    • 77955419648 scopus 로고    scopus 로고
    • Particle swarm optimization aided orthogonal forward regression for unified data modeling
    • Aug.
    • S. Chen, X. Hong, and C. J. Harris, "Particle swarm optimization aided orthogonal forward regression for unified data modeling," IEEE Trans. Evol. Comput., vol. 14, no. 4, pp. 477-499, Aug. 2010.
    • (2010) IEEE Trans. Evol. Comput. , vol.14 , Issue.4 , pp. 477-499
    • Chen, S.1    Hong, X.2    Harris, C.J.3
  • 36
    • 57749092656 scopus 로고    scopus 로고
    • A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks
    • Dec.
    • D. S. Huang and J. X. Du, "A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks," IEEE Trans. Neural Netw., vol. 19, no. 12, pp. 2099-2115, Dec. 2008.
    • (2008) IEEE Trans. Neural Netw. , vol.19 , Issue.12 , pp. 2099-2115
    • Huang, D.S.1    Du, J.X.2
  • 37
    • 82655162109 scopus 로고    scopus 로고
    • Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution
    • S. K. Oh, W. D. Kim, W. Pedrycz, and S. C. Joo, "Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution," Neurocomputing, vol. 78, no. 1, pp. 121-132, 2012.
    • (2012) Neurocomputing , vol.78 , Issue.1 , pp. 121-132
    • Oh, S.K.1    Kim, W.D.2    Pedrycz, W.3    Joo, S.C.4
  • 38
    • 26944447534 scopus 로고    scopus 로고
    • Nonlinear adaptive model predictive control based on self-correcting neural network models
    • A. Alexandridis and H. Sarimveis, "Nonlinear adaptive model predictive control based on self-correcting neural network models," AIChE J., vol. 51, no. 9, pp. 2495-2506, 2005.
    • (2005) AIChE J. , vol.51 , Issue.9 , pp. 2495-2506
    • Alexandridis, A.1    Sarimveis, H.2
  • 40
    • 12844283500 scopus 로고    scopus 로고
    • A two-stage evolutionary algorithm for variable selection in the development of RBF neural network models
    • A. Alexandridis, P. Patrinos, H. Sarimveis, and G. Tsekouras, "A two-stage evolutionary algorithm for variable selection in the development of RBF neural network models," Chemometrics Intell. Lab. Syst., vol. 75, no. 2, pp. 149-162, 2005.
    • (2005) Chemometrics Intell. Lab. Syst. , vol.75 , Issue.2 , pp. 149-162
    • Alexandridis, A.1    Patrinos, P.2    Sarimveis, H.3    Tsekouras, G.4
  • 41
    • 77958043391 scopus 로고    scopus 로고
    • Variable selection in nonlinear modeling based on RBF networks and evolutionary computation
    • P. Patrinos, A. Alexandridis, K. Ninos, and H. Sarimveis, "Variable selection in nonlinear modeling based on RBF networks and evolutionary computation," Int. J. Neural Syst., vol. 20, no. 5, pp. 365-379, 2010.
    • (2010) Int. J. Neural Syst. , vol.20 , Issue.5 , pp. 365-379
    • Patrinos, P.1    Alexandridis, A.2    Ninos, K.3    Sarimveis, H.4
  • 42
    • 84860403078 scopus 로고    scopus 로고
    • A neural network approach for the prediction of the refractive index based on experimental data
    • A. Alexandridis, E. Chondrodima, K. Moutzouris, and D. Triantis, "A neural network approach for the prediction of the refractive index based on experimental data," J. Mater. Sci., vol. 47, no. 2, pp. 883-891, 2012.
    • (2012) J. Mater. Sci. , vol.47 , Issue.2 , pp. 883-891
    • Alexandridis, A.1    Chondrodima, E.2    Moutzouris, K.3    Triantis, D.4
  • 43
    • 84855172966 scopus 로고    scopus 로고
    • A neural network approach for compressive strength prediction in cement-based materials through the study of pressure-stimulated electrical signals
    • May
    • A. Alexandridis, D. Triantis, I. Stavrakas, and C. Stergiopoulos, "A neural network approach for compressive strength prediction in cement-based materials through the study of pressure-stimulated electrical signals," Construct. Build. Mater., vol. 30, pp. 294-300, May 2012.
    • (2012) Construct. Build. Mater. , vol.30 , pp. 294-300
    • Alexandridis, A.1    Triantis, D.2    Stavrakas, I.3    Stergiopoulos, C.4
  • 44
    • 0031139892 scopus 로고    scopus 로고
    • Fuzzy control of multivariable nonlinear servomechanisms with explicit decoupling scheme
    • May
    • J. Nie, "Fuzzy control of multivariable nonlinear servomechanisms with explicit decoupling scheme," IEEE Trans. Fuzzy Syst., vol. 5, no. 2, pp. 304-311, May 1997.
    • (1997) IEEE Trans. Fuzzy Syst. , vol.5 , Issue.2 , pp. 304-311
    • Nie, J.1
  • 48
    • 10044295997 scopus 로고    scopus 로고
    • A fuzzy system modeling algorithm for data analysis and approximate reasoning
    • K. Kilic, B. A. Sproule, I. B. Türksen, and C. A. Naranjo, "A fuzzy system modeling algorithm for data analysis and approximate reasoning," Robot. Auton. Syst., vol. 49, nos. 3-4, pp. 173-180, 2004.
    • (2004) Robot. Auton. Syst. , vol.49 , Issue.3-4 , pp. 173-180
    • Kilic, K.1    Sproule, B.A.2    Türksen, I.B.3    Naranjo, C.A.4
  • 49
    • 0002432565 scopus 로고
    • Multivariate adaptive regression splines
    • J. Friedman, "Multivariate adaptive regression splines," Ann. Stat., vol. 19, no. 1, pp. 1-67, 1991.
    • (1991) Ann. Stat. , vol.19 , Issue.1 , pp. 1-67
    • Friedman, J.1
  • 50
    • 34047166022 scopus 로고    scopus 로고
    • Support vector echo-state machine for chaotic time-series prediction
    • Mar.
    • Z. Shi and M. Han, "Support vector echo-state machine for chaotic time-series prediction," IEEE Trans. Neural Netw., vol. 18, no. 2, pp. 359-372, Mar. 2007.
    • (2007) IEEE Trans. Neural Netw. , vol.18 , Issue.2 , pp. 359-372
    • Shi, Z.1    Han, M.2
  • 51
    • 0033640675 scopus 로고    scopus 로고
    • Bayesian wavelet networks for nonparametric regression
    • Jan.
    • C. C. Holmes and B. K. Mallick, "Bayesian wavelet networks for nonparametric regression," IEEE Trans. Neural Netw., vol. 11, no. 1, pp. 27-35, Jan. 2000.
    • (2000) IEEE Trans. Neural Netw. , vol.11 , Issue.1 , pp. 27-35
    • Holmes, C.C.1    Mallick, B.K.2
  • 52
    • 9244228528 scopus 로고    scopus 로고
    • Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure
    • Nov.
    • C. K. Loo, M. Rajeswari, and M. V. C. Rao, "Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure," IEEE Trans. Neural Netw., vol. 15, no. 6, pp. 1378-1395, Nov. 2004.
    • (2004) IEEE Trans. Neural Netw. , vol.15 , Issue.6 , pp. 1378-1395
    • Loo, C.K.1    Rajeswari, M.2    Rao, M.V.C.3
  • 53
    • 0025750495 scopus 로고
    • Backpropagation with expected source values
    • T. Samad, "Backpropagation with expected source values," Neural Netw., vol. 4, no. 5, pp. 615-618, 1991.
    • (1991) Neural Netw. , vol.4 , Issue.5 , pp. 615-618
    • Samad, T.1
  • 54
    • 0028543366 scopus 로고
    • Training feedforward networks with the Marquardt algorithm
    • Nov.
    • M. T. Hagan and M. Menhaj, "Training feedforward networks with the Marquardt algorithm," IEEE Trans. Neural Netw., vol. 5, no. 6, pp. 989-993, Nov. 1994.
    • (1994) IEEE Trans. Neural Netw. , vol.5 , Issue.6 , pp. 989-993
    • Hagan, M.T.1    Menhaj, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.