메뉴 건너뛰기




Volumn 14, Issue 9, 2010, Pages 953-971

CO2RBFN: An evolutionary cooperative-competitive RBFN design algorithm for classification problems

Author keywords

Classification; Cooperative Competitive Evolutionary Design; Evolutionary Algorithms; Fuzzy Rule Base Systems; Radial Basis Function Networks

Indexed keywords

CLASSIFICATION; COMPETITIVE ALGORITHMS; COMPETITIVE ENVIRONMENT; CREDIT ASSIGNMENT; DISTANCE MEASURE; EVOLUTIONARY DESIGN; FUZZY RULE BASE; FUZZY RULE BASED SYSTEMS; LOCAL ERROR; NOMINAL FEATURE; RADIAL BASIS FUNCTIONS; SOFT COMPUTING METHODS;

EID: 77951795476     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-009-0488-z     Document Type: Article
Times cited : (26)

References (82)
  • 2
    • 0036738759 scopus 로고    scopus 로고
    • Two highly efficient second-order algorithms for training feedforwards networks
    • Ampazis N, Perantonis SJ (2002) Two highly efficient second-order algorithms for training feedforwards networks. IEEE Trans Neural Netw 13(3): 1064-1074.
    • (2002) IEEE Trans Neural Netw , vol.13 , Issue.3 , pp. 1064-1074
    • Ampazis, N.1    Perantonis, S.J.2
  • 3
    • 56549113284 scopus 로고    scopus 로고
    • UCI machine learning repository
    • University of California, Irvine, CA
    • Asuncion A, Newman DJ (2007) UCI machine learning repository. School of Information and Computer Science, University of California, Irvine, CA. http://www. ics. uci. edu/~mlearn/MLRepository. html.
    • (2007) School of Information and Computer Science
    • Asuncion, A.1    Newman, D.J.2
  • 4
    • 0031122888 scopus 로고    scopus 로고
    • Evolutionary computation: Comments on the history and current state
    • Bäck T, Hammel U, Schwefel H (1997) Evolutionary computation: comments on the history and current state. IEEE Trans Evol Comput 1(1): 3-17.
    • (1997) IEEE Trans Evol Comput , vol.1 , Issue.1 , pp. 3-17
    • Bäck, T.1    Hammel, U.2    Schwefel, H.3
  • 6
    • 0028835062 scopus 로고
    • Radial basis function network configuration using genetic algorithms
    • Billings SA, Zheng GL (1995) Radial basis function network configuration using genetic algorithms. Neural Netw 8(6): 877-890.
    • (1995) Neural Netw , vol.8 , Issue.6 , pp. 877-890
    • Billings, S.A.1    Zheng, G.L.2
  • 7
    • 0000621802 scopus 로고
    • Multivariable functional interpolation and adaptive networks
    • Broomhead D, Lowe D (1988) Multivariable functional interpolation and adaptive networks. Complex Syst 2: 321-355.
    • (1988) Complex Syst , vol.2 , pp. 321-355
    • Broomhead, D.1    Lowe, D.2
  • 8
    • 26844578765 scopus 로고    scopus 로고
    • Evolutionary optimization of radial basis function classifiers for data mining applications
    • Buchtala O, Klimek M, Sick B (2005) Evolutionary optimization of radial basis function classifiers for data mining applications. IEEE Trans Syst Man Cybern B 35(5): 928-947.
    • (2005) IEEE Trans Syst Man Cybern B , vol.35 , Issue.5 , pp. 928-947
    • Buchtala, O.1    Klimek, M.2    Sick, B.3
  • 11
    • 0025669403 scopus 로고
    • Practical identification of narmax models using radial basis functions
    • Chen S, Billings SA, Cowan CFN, Grant PW (1990) Practical identification of narmax models using radial basis functions. Int J Control 52(6): 1327-1350.
    • (1990) Int J Control , vol.52 , Issue.6 , pp. 1327-1350
    • Chen, S.1    Billings, S.A.2    Cowan, C.F.N.3    Grant, P.W.4
  • 12
    • 0026116468 scopus 로고
    • Orthogonal least squares learning algorithm for radial basis function networks
    • Chen S, Cowan C, Grant P (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Netw 2: 302-309.
    • (1991) IEEE Trans Neural Netw , vol.2 , pp. 302-309
    • Chen, S.1    Cowan, C.2    Grant, P.3
  • 13
    • 0032594851 scopus 로고    scopus 로고
    • Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks
    • Chen S, Wu Y, Luk BL (1999) Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks. IEEE Trans Neural Netw 10(5): 1239-1243.
    • (1999) IEEE Trans Neural Netw , vol.10 , Issue.5 , pp. 1239-1243
    • Chen, S.1    Wu, Y.2    Luk, B.L.3
  • 14
  • 17
    • 29644438050 scopus 로고    scopus 로고
    • Statistical Comparisons of Classifiers over Multiple Data Sets
    • Demšar J (2006) Statistical Comparisons of Classifiers over Multiple Data Sets. J Mach Learn Res 7: 1-30.
    • (2006) J Mach Learn Res , vol.7 , pp. 1-30
    • Demšar, J.1
  • 18
    • 40649090413 scopus 로고    scopus 로고
    • Time series prediction using evolving radial basis function networks with new enconding scheme
    • Du H, Zhang N (2008) Time series prediction using evolving radial basis function networks with new enconding scheme. Neurocomputing 71: 1388-1400.
    • (2008) Neurocomputing , vol.71 , pp. 1388-1400
    • Du, H.1    Zhang, N.2
  • 19
    • 19344375792 scopus 로고    scopus 로고
    • High-speed face recognition base on discrete cosine transform and RBF neural networks
    • Er MJ, Chen W, Wu S (2005) High-speed face recognition base on discrete cosine transform and RBF neural networks. IEEE Trans Neural Netw 16(3): 679-691.
    • (2005) IEEE Trans Neural Netw , vol.16 , Issue.3 , pp. 679-691
    • Er, M.J.1    Chen, W.2    Wu, S.3
  • 20
    • 2442452950 scopus 로고    scopus 로고
    • Classical resemblance measures
    • Exploratory methods for extracting statistical information from complex data, Series: studies in classification, data analysis, and knowledge organization, Springer, Berlin
    • Esposito F, Malerba D, Tamma V, Bock HH (2000a) Classical resemblance measures. In: Bock H-H, Diday E (eds) Analysis of symbolic data. Exploratory methods for extracting statistical information from complex data, Series: studies in classification, data analysis, and knowledge organization, vol 15. Springer, Berlin, pp 139-152.
    • (2000) Analysis of Symbolic Data , vol.15 , pp. 139-152
    • Esposito, F.1    Malerba, D.2    Tamma, V.3    Bock, H.H.4
  • 21
    • 0034233438 scopus 로고    scopus 로고
    • Approximation of continuous and discontinuous mappings by a growing neural RBF-based algorithm
    • Esposito A, Marinaro M, Oricchio D, Scarpetta S (2000b) Approximation of continuous and discontinuous mappings by a growing neural RBF-based algorithm. Neural Netw 13(6): 651-665.
    • (2000) Neural Netw , vol.13 , Issue.6 , pp. 651-665
    • Esposito, A.1    Marinaro, M.2    Oricchio, D.3    Scarpetta, S.4
  • 22
    • 0344927103 scopus 로고    scopus 로고
    • Genetic assisted selection of RBF model structures for greenhouse inside air temperature prediction
    • Ferreira PM, Ruano AE, Fonseca CM (2003) Genetic assisted selection of RBF model structures for greenhouse inside air temperature prediction. IEEE Control Appl 1: 576-581.
    • (2003) IEEE Control Appl , vol.1 , pp. 576-581
    • Ferreira, P.M.1    Ruano, A.E.2    Fonseca, C.M.3
  • 24
    • 84901425408 scopus 로고    scopus 로고
    • A GA-based novel RBF classifier with class-dependent features
    • Fu X, Wang L (2002) A GA-based novel RBF classifier with class-dependent features. Proc Congr Evol Comput 2: 1964-1969.
    • (2002) Proc Congr Evol Comput , vol.2 , pp. 1964-1969
    • Fu, X.1    Wang, L.2
  • 25
    • 0037983742 scopus 로고    scopus 로고
    • Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance
    • Fu X, Wang L (2003) Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance. IEEE Trans Syst Man Cybern B 33(3): 399-409.
    • (2003) IEEE Trans Syst Man Cybern B , vol.33 , Issue.3 , pp. 399-409
    • Fu, X.1    Wang, L.2
  • 27
    • 0001903624 scopus 로고
    • Genetic algorithms with sharing for multimodal function optimization
    • In: Grefenstette (ed) Lawrence Erlbaum Associates
    • Goldberg D, Richardson J (1987) Genetic algorithms with sharing for multimodal function optimization. In: Grefenstette (ed) Proceedings of second international conference on genetic algorithms. Lawrence Erlbaum Associates, pp 41-49.
    • (1987) Proceedings of second international conference on genetic algorithms , pp. 41-49
    • Goldberg, D.1    Richardson, J.2
  • 28
    • 0004236492 scopus 로고    scopus 로고
    • 3rd edn. J. Hopkins University Press, Baltimore
    • Golub G, van Loan C (1996) Matrix computations, 3rd edn. J. Hopkins University Press, Baltimore.
    • (1996) Matrix computations
    • Golub, G.1    van Loan, C.2
  • 29
    • 0742321288 scopus 로고    scopus 로고
    • Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation
    • González J, Rojas I, Ortega J, Pomares H, Fernández FJ, Díaz AF (2003) Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation. IEEE Trans Neural Netw 14(6): 1478-1495.
    • (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
  • 31
    • 6344287812 scopus 로고    scopus 로고
    • A review of genetic algorithms applied to training radial basis function networks
    • Harpham C, Dawson C, Brown M (2004) A review of genetic algorithms applied to training radial basis function networks. Neural Comput Appl 13: 193-201.
    • (2004) Neural Comput Appl , vol.13 , pp. 193-201
    • Harpham, C.1    Dawson, C.2    Brown, M.3
  • 32
    • 0026373082 scopus 로고
    • Local training for radial basis function networks: Towards solving the hidden unit problem
    • In:Boston
    • Holcomb T, Morari M (1991) Local training for radial basis function networks: towards solving the hidden unit problem. In: Proceedings of American control conference, Boston.
    • (1991) Proceedings of American Control Conference
    • Holcomb, T.1    Morari, M.2
  • 34
    • 38649125283 scopus 로고    scopus 로고
    • Adaptive neural network algorithm for control design of rigid-link electrically driven robots
    • Huang SN, Tan KK, Lee TH (2008) Adaptive neural network algorithm for control design of rigid-link electrically driven robots. Neurocomputing 71(4-6): 885-894.
    • (2008) Neurocomputing , vol.71 , Issue.4-6 , pp. 885-894
    • Huang, S.N.1    Tan, K.K.2    Lee, T.H.3
  • 35
    • 0027266182 scopus 로고
    • Functional equivalence between radial basis functions and fuzzy inference systems
    • Jang JSR, Sun CT (1993) Functional equivalence between radial basis functions and fuzzy inference systems. IEEE Trans Neural Netw 4: 156-158.
    • (1993) IEEE Trans Neural Netw , vol.4 , pp. 156-158
    • Jang, J.S.R.1    Sun, C.T.2
  • 36
    • 0037226313 scopus 로고    scopus 로고
    • Design of structural modular neural networks with genetic algorithm
    • Jiang N, Zhao ZY, Ren LQ (2003) Design of structural modular neural networks with genetic algorithm. Adv Eng Soft 1: 17-24.
    • (2003) Adv Eng Soft , vol.1 , pp. 17-24
    • Jiang, N.1    Zhao, Z.Y.2    Ren, L.Q.3
  • 37
    • 0038173250 scopus 로고    scopus 로고
    • Extracting interpretable fuzzy rules from RBF networks
    • Jin Y, Sendhoff B (2003) Extracting interpretable fuzzy rules from RBF networks. Neural Process Lett 17(2): 149-164.
    • (2003) Neural Process Lett , vol.17 , Issue.2 , pp. 149-164
    • Jin, Y.1    Sendhoff, B.2
  • 38
    • 17744373086 scopus 로고    scopus 로고
    • Evolutionary radial functions for credit assessment
    • Lacerda E, Carvalho A, Braga A, Ludermir T (2005) Evolutionary radial functions for credit assessment. Appl Intell 22: 167-181.
    • (2005) Appl Intell , vol.22 , pp. 167-181
    • Lacerda, E.1    Carvalho, A.2    Braga, A.3    Ludermir, T.4
  • 39
    • 0025839504 scopus 로고
    • A Gaussian potential function network with hierarchically seft-organising learning
    • Lee S, Kil RM (1991) A Gaussian potential function network with hierarchically seft-organising learning. Neural Netw 4: 207-224.
    • (1991) Neural Netw , vol.4 , pp. 207-224
    • Lee, S.1    Kil, R.M.2
  • 40
    • 0036254949 scopus 로고    scopus 로고
    • Detection of small objects in clutter using a GA-RBF neural network
    • Leung H, Dubash N, Xie N (2002) Detection of small objects in clutter using a GA-RBF neural network. IEEE Trans Aero Electr Sys 38(1): 98-118.
    • (2002) IEEE Trans Aero Electr Sys , vol.38 , Issue.1 , pp. 98-118
    • Leung, H.1    Dubash, N.2    Xie, N.3
  • 41
    • 38349047621 scopus 로고    scopus 로고
    • Improving multiclass pattern recognition with a co-evolutionary RBFNN
    • Li M, Tian J, Chen F (2008) Improving multiclass pattern recognition with a co-evolutionary RBFNN. Pattern Recogn Lett 29(4): 392-406.
    • (2008) Pattern Recogn Lett , vol.29 , Issue.4 , pp. 392-406
    • Li, M.1    Tian, J.2    Chen, F.3
  • 43
    • 0016451032 scopus 로고
    • An experiment in linguistic synthesis with a fuzzy logic controller
    • Mandani E, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7(1): 1-13.
    • (1975) Int J Man Mach Stud , vol.7 , Issue.1 , pp. 1-13
    • Mandani, E.1    Assilian, S.2
  • 44
    • 41149089754 scopus 로고    scopus 로고
    • Radial basis function classifiers to help in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry
    • Marcos JV, Hornero R, Álvarez D, Del Campo F, López M, Zamarrón C (2008) Radial basis function classifiers to help in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry. Med Biol Eng Comput 46: 323-332.
    • (2008) Med Biol Eng Comput , vol.46 , pp. 323-332
    • Marcos, J.V.1    Hornero, R.2    Álvarez, D.3    Del Campo, F.4    López, M.5    Zamarrón, C.6
  • 45
    • 6344254665 scopus 로고    scopus 로고
    • Combined genetic algorithms and neural network approach for power system transient stability evaluation
    • Moechtar M, Farag AS, Hu L, Cheng TC (1999) Combined genetic algorithms and neural network approach for power system transient stability evaluation. Europ Trans Elect Power 9(2): 115-122.
    • (1999) Europ Trans Elect Power , vol.9 , Issue.2 , pp. 115-122
    • Moechtar, M.1    Farag, A.S.2    Hu, L.3    Cheng, T.C.4
  • 46
    • 0000672424 scopus 로고
    • Fast learning in networks of locally-tuned processing units
    • Moody J, Darken CJ (1989) Fast learning in networks of locally-tuned processing units. Neural Comput 1: 281-294.
    • (1989) Neural Comput , vol.1 , pp. 281-294
    • Moody, J.1    Darken, C.J.2
  • 48
    • 27544458557 scopus 로고    scopus 로고
    • Learning methods for radial basis function networks
    • Neruda R, Kudová P (2005) Learning methods for radial basis function networks. Future Gener Comp Sy 21(7): 1131-1142.
    • (2005) Future Gener Comp Sy , vol.21 , Issue.7 , pp. 1131-1142
    • Neruda, R.1    Kudová, P.2
  • 49
    • 33751560009 scopus 로고
    • Regularization on the selection of radial basis function centers
    • Orr MJL (1995) Regularization on the selection of radial basis function centers. Neural Comput 7: 606-623.
    • (1995) Neural Comput , vol.7 , pp. 606-623
    • Orr, M.J.L.1
  • 50
    • 0000106040 scopus 로고
    • Universal approximation using radial-basis function networks
    • Park J, Sandberg I (1991) Universal approximation using radial-basis function networks. Neural Comput 3: 246-257.
    • (1991) Neural Comput , vol.3 , pp. 246-257
    • Park, J.1    Sandberg, I.2
  • 51
    • 0001002401 scopus 로고
    • Universal approximation and radial basis function network
    • Park J, Sandberg I (1993) Universal approximation and radial basis function network. Neural Comput 5(2): 305-316.
    • (1993) Neural Comput , vol.5 , Issue.2 , pp. 305-316
    • Park, J.1    Sandberg, I.2
  • 52
    • 0032122726 scopus 로고    scopus 로고
    • Conditional fuzzy clustering in the design of radial basis function neural networks
    • Pedrycz W (1998) Conditional fuzzy clustering in the design of radial basis function neural networks. IEEE Trans Neural Netw 9(4): 601-612.
    • (1998) IEEE Trans Neural Netw , vol.9 , Issue.4 , pp. 601-612
    • Pedrycz, W.1
  • 53
    • 37249029174 scopus 로고    scopus 로고
    • A hybrid forward algorithm for RBF neural network construction
    • Peng JX, Li K, Huang DS (2006) A hybrid forward algorithm for RBF neural network construction. IEEE Trans Neural Netw 17(6): 1439-1451.
    • (2006) IEEE Trans Neural Netw , vol.17 , Issue.6 , pp. 1439-1451
    • Peng, J.X.1    Li, K.2    Huang, D.S.3
  • 56
    • 0001071040 scopus 로고
    • A resource Allocating Network for Function Interpolation
    • Plat J (1991) A resource allocating network for function interpolation. Neural Comput 3(2): 213-225.
    • (1991) Neural Comput , vol.3 , Issue.2 , pp. 213-225
    • Plat, J.1
  • 57
    • 0034153728 scopus 로고    scopus 로고
    • Cooperative coevolution: An architecture for evolving coadapted subcomponents
    • Potter M, De Jong K (2000) Cooperative coevolution: an architecture for evolving coadapted subcomponents. Evol Comput 8(1): 1-29.
    • (2000) Evol Comput , vol.8 , Issue.1 , pp. 1-29
    • Potter, M.1    de Jong, K.2
  • 62
    • 33847224122 scopus 로고    scopus 로고
    • A new Hybrid Methodology for Cooperative-Coevolutionary Optimization of Radial Basis Function Networks
    • doi: 10. 1007/s00500-006-0128-9
    • Rivera AJ, Rojas I, Ortega J, del Jesus MJ (2007) A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks. Soft Comput. doi: 10. 1007/s00500-006-0128-9.
    • (2007) Soft Comput
    • Rivera, A.J.1    Rojas, I.2    Ortega, J.3    del Jesus, M.J.4
  • 64
    • 25144499903 scopus 로고    scopus 로고
    • Statisctical analysis of the main parameters in the definition of radial basis function networks
    • Rojas I, Valenzuela O, Prieto A (1997) Statisctical analysis of the main parameters in the definition of radial basis function networks. Lect Notes Comput Sci 1240: 882-891.
    • (1997) Lect Notes Comput Sci , vol.1240 , pp. 882-891
    • Rojas, I.1    Valenzuela, O.2    Prieto, A.3
  • 65
    • 0036131648 scopus 로고    scopus 로고
    • A searching for a solution to the automatic RBF network design problem
    • Sanchez VD (2002) A searching for a solution to the automatic RBF network design problem. Neurocomputing 42: 147-170.
    • (2002) Neurocomputing , vol.42 , pp. 147-170
    • Sanchez, V.D.1
  • 68
    • 0035307307 scopus 로고    scopus 로고
    • Time-series forecasting using GA-tuned radial basis functions
    • Sheta AF, De Jong K (2001) Time-series forecasting using GA-tuned radial basis functions. Info Sci 133(3-4): 221-228.
    • (2001) Info Sci , vol.133 , Issue.3-4 , pp. 221-228
    • Sheta, A.F.1    de Jong, K.2
  • 69
    • 0022909661 scopus 로고
    • Towards memory-based reasoning, Commun
    • Stanfill C, Waltz D (1986) Towards memory-based reasoning, Commun. ACM 29(12): 1213-1228.
    • (1986) Acm , vol.29 , Issue.12 , pp. 1213-1228
    • Stanfill, C.1    Waltz, D.2
  • 70
    • 0346525901 scopus 로고    scopus 로고
    • Design of a soft computing hybrid model classifier for data mining applications
    • Sumathi S, Sivanandam SN, Ravindran R (2001) Design of a soft computing hybrid model classifier for data mining applications. Engin Intell Sys Electr Engin Comm 9(1): 33-56.
    • (2001) Engin Intell Sys Electr Engin Comm , vol.9 , Issue.1 , pp. 33-56
    • Sumathi, S.1    Sivanandam, S.N.2    Ravindran, R.3
  • 71
    • 17444384843 scopus 로고    scopus 로고
    • Optimal partition algorithm of the RBF neural network and its application to financial time series forecasting
    • Sun YF, Liang YC, Zhang WL, Lee HP, Lin WZ, Cao LJ (2005) Optimal partition algorithm of the RBF neural network and its application to financial time series forecasting. Neural Comput Appl 14(1): 36-44.
    • (2005) Neural Comput Appl , vol.14 , Issue.1 , pp. 36-44
    • Sun, Y.F.1    Liang, Y.C.2    Zhang, W.L.3    Lee, H.P.4    Lin, W.Z.5    Cao, L.J.6
  • 73
    • 38349010878 scopus 로고    scopus 로고
    • A soft-computing methodology for noninvasive time-spatial temperature estimation
    • Teixeira CA, Ruano MG, Ruano AE, Pereira WCA (2008) A soft-computing methodology for noninvasive time-spatial temperature estimation. IEEE Trans Bio Med Eng 55(2): 572-580.
    • (2008) IEEE Trans Bio Med Eng , vol.55 , Issue.2 , pp. 572-580
    • Teixeira, C.A.1    Ruano, M.G.2    Ruano, A.E.3    Pereira, W.C.A.4
  • 75
    • 0343603384 scopus 로고    scopus 로고
    • Model selection using a simplex reproduction genetic algorithm
    • Vesin JM, Gruter R (1999) Model selection using a simplex reproduction genetic algorithm. Sig Process 78: 321-327.
    • (1999) Sig Process , vol.78 , pp. 321-327
    • Vesin, J.M.1    Gruter, R.2
  • 76
    • 0030197198 scopus 로고    scopus 로고
    • Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction
    • Whitehead B, Choate T (1996) Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction. IEEE Trans Neural Netw 7(4): 869-880.
    • (1996) IEEE Trans Neural Netw , vol.7 , Issue.4 , pp. 869-880
    • Whitehead, B.1    Choate, T.2
  • 77
    • 0025488663 scopus 로고
    • 30 Years of adaptive neural networks: Perceptron, madaline and backpropagation
    • Widrow B, Lehr MA (1990) 30 Years of adaptive neural networks: perceptron, madaline and backpropagation. Proc IEEE 78(9): 1415-1442.
    • (1990) Proc IEEE , vol.78 , Issue.9 , pp. 1415-1442
    • Widrow, B.1    Lehr, M.A.2
  • 78
    • 0001899045 scopus 로고    scopus 로고
    • Improved heterogeneous distance functions
    • Wilson DR, Martinez TR (1997) Improved heterogeneous distance functions. J Artif Intell Res 6(1): 1-34.
    • (1997) J Artif Intell Res , vol.6 , Issue.1 , pp. 1-34
    • Wilson, D.R.1    Martinez, T.R.2
  • 79
    • 0347090991 scopus 로고    scopus 로고
    • Dynamics modelling of fluid power systems applying a global error descent algorithm to a selforganising radial basis function network
    • Xue Y, Watton J (1998) Dynamics modelling of fluid power systems applying a global error descent algorithm to a selforganising radial basis function network. Mechatronics 8(7): 727-745.
    • (1998) Mechatronics , vol.8 , Issue.7 , pp. 727-745
    • Xue, Y.1    Watton, J.2
  • 80
    • 0027574256 scopus 로고
    • A review of evolutionary artificial neural networks
    • Yao X (1993) A review of evolutionary artificial neural networks. Int J Intell Syst 8(4): 539-567.
    • (1993) Int J Intell Syst , vol.8 , Issue.4 , pp. 539-567
    • Yao, X.1
  • 81
    • 0033362601 scopus 로고    scopus 로고
    • Evolving artificial neural networks
    • Yao X (1999) Evolving artificial neural networks. Proc IEEE 87(9): 1423-1447.
    • (1999) Proc IEEE , vol.87 , Issue.9 , pp. 1423-1447
    • Yao, X.1
  • 82
    • 33845300246 scopus 로고    scopus 로고
    • Multi-Objective evolutionary algorithm for radial basis function neural network design
    • Yen GG (2006) Multi-Objective evolutionary algorithm for radial basis function neural network design. Stud Comput Intell 16: 221-239.
    • (2006) Stud Comput Intell , vol.16 , pp. 221-239
    • Yen, G.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.