메뉴 건너뛰기




Volumn 39, Issue 3, 2009, Pages 705-722

A new adaptive merging and growing algorithm for designing artificial neural networks

Author keywords

Adding neurons; Artificial neural network (ANN) design; Generalization ability; Merging neurons; Retraining

Indexed keywords

ADAPTIVE STRATEGIES; ADDING NEURONS; ARTIFICIAL NEURAL NETWORK (ANN) DESIGN; BENCH-MARK PROBLEMS; BREAST CANCERS; CAN DESIGNS; CREDIT CARDS; DESIGN PROCESS; FIXED STRATEGIES; GENERALIZATION ABILITY; HIDDEN NEURONS; LEARNING ABILITIES; MACHINE-LEARNING; MERGE OPERATIONS; MIXED-MODE OPERATIONS; OTHER ALGORITHMS; RETRAINING; TRAINING PROCESS;

EID: 67349203854     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2008.2008724     Document Type: Article
Times cited : (115)

References (77)
  • 1
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • I, D. E. Rumelhart and J. L. McClelland, Eds. Cambridge, MA: MIT Press
    • D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing, vol. I, D. E. Rumelhart and J. L. McClelland, Eds. Cambridge, MA: MIT Press, 1986, pp. 318-362.
    • (1986) Parallel Distributed Processing, vol , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 2
    • 0031146959 scopus 로고    scopus 로고
    • Constructive algorithms for structure learning in feedforward neural networks for regression problems
    • May
    • T. Y. Kwok and D. Y. Yeung, "Constructive algorithms for structure learning in feedforward neural networks for regression problems," IEEE Trans. Neural Netw., vol. 8, no. 3, pp. 630-645, May 1997.
    • (1997) IEEE Trans. Neural Netw , vol.8 , Issue.3 , pp. 630-645
    • Kwok, T.Y.1    Yeung, D.Y.2
  • 3
    • 0027662338 scopus 로고
    • Pruning algorithms - A survey
    • Sep
    • R. Reed, "Pruning algorithms - A survey," IEEE Trans. Neural Netw. vol. 4, no. 5, pp. 740-747, Sep. 1993.
    • (1993) IEEE Trans. Neural Netw , vol.4 , Issue.5 , pp. 740-747
    • Reed, R.1
  • 4
    • 0001219859 scopus 로고
    • Regularization theory and neural networks architectures
    • Mar
    • F. Girosi, M. Jones, and T. Poggio, "Regularization theory and neural networks architectures," Neural Comput., vol. 7, no. 2, pp. 219-269, Mar. 1995.
    • (1995) Neural Comput , vol.7 , Issue.2 , pp. 219-269
    • Girosi, F.1    Jones, M.2    Poggio, T.3
  • 9
    • 0000539096 scopus 로고
    • Generalization by weight-elimination with application to forecasting
    • R. Lippmann, J. Moody, and D. S. Touretzky, Eds
    • A. S. Weigend, D. E. Rumelhart, and B. A. Huberman, "Generalization by weight-elimination with application to forecasting," in Proc. Advances Neural Inform. Process. Syst., R. Lippmann, J. Moody, and D. S. Touretzky, Eds., 1991, vol. 3, pp. 875-882.
    • (1991) Proc. Advances Neural Inform. Process. Syst , vol.3 , pp. 875-882
    • Weigend, A.S.1    Rumelhart, D.E.2    Huberman, B.A.3
  • 10
    • 67349107001 scopus 로고    scopus 로고
    • Two strategies to avoid overfitting in feedforward neural networks
    • C. Schittenkopf, G. Deco, and W. Brauer, "Two strategies to avoid overfitting in feedforward neural networks," Neural Netw., vol. 10, pp. 804-818, 1997.
    • (1997) Neural Netw , vol.10 , pp. 804-818
    • Schittenkopf, C.1    Deco, G.2    Brauer, W.3
  • 11
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • May
    • D. J. C. MacKay, "Bayesian interpolation," Neural Comput., vol. 4, no. 3, pp. 415-447, May 1992.
    • (1992) Neural Comput , vol.4 , Issue.3 , pp. 415-447
    • MacKay, D.J.C.1
  • 12
    • 33644884686 scopus 로고    scopus 로고
    • A node pruning algorithm based on a Fourier amplitude sensitivity test method
    • Mar
    • P. Lauret, E. Fock, and T. A. Mara, "A node pruning algorithm based on a Fourier amplitude sensitivity test method," IEEE Trans. Neural Netw., vol. 17, no. 2, pp. 273-293, Mar. 2006.
    • (2006) IEEE Trans. Neural Netw , vol.17 , Issue.2 , pp. 273-293
    • Lauret, P.1    Fock, E.2    Mara, T.A.3
  • 13
    • 0002704818 scopus 로고
    • A practical Bayesian framework for backpropagation networks
    • May
    • D. J. C. MacKay, "A practical Bayesian framework for backpropagation networks," Neural Comput., vol. 4, no. 3, pp. 448-472, May 1992.
    • (1992) Neural Comput , vol.4 , Issue.3 , pp. 448-472
    • MacKay, D.J.C.1
  • 14
    • 0028202641 scopus 로고
    • An evolutionary algorithm that constructs recurrent neural networks
    • Jan
    • P. J. Angeline, G. M. Saunders, and J. B. Pollack, "An evolutionary algorithm that constructs recurrent neural networks," IEEE Trans. Neural Netw., vol. 5, no. 1, pp. 54-65, Jan. 1994.
    • (1994) IEEE Trans. Neural Netw , vol.5 , Issue.1 , pp. 54-65
    • Angeline, P.J.1    Saunders, G.M.2    Pollack, J.B.3
  • 16
    • 0001958391 scopus 로고
    • Study of a growth algorithm for a feedforwaed network
    • J. P. Nadal, "Study of a growth algorithm for a feedforwaed network," Int. J. Neural Syst., vol. 1, no. 1, pp. 55-59, 1989.
    • (1989) Int. J. Neural Syst , vol.1 , Issue.1 , pp. 55-59
    • Nadal, J.P.1
  • 17
    • 0028390208 scopus 로고
    • A constructive algorithm that converges for real-valued input patterns
    • Mar
    • N. Burgess. "A constructive algorithm that converges for real-valued input patterns," Int. J. Neural Syst., vol. 5, no. 1, pp. 59-66, Mar. 1994.
    • (1994) Int. J. Neural Syst , vol.5 , Issue.1 , pp. 59-66
    • Burgess, N.1
  • 18
    • 0029185114 scopus 로고
    • Use of a quasi-Newton method in a feedforward neural network construction algorithm
    • Jan
    • R. Setiono and L. C. K. Hui, "Use of a quasi-Newton method in a feedforward neural network construction algorithm," IEEE Trans. Neural Netw., vol. 6, no. 1, pp. 273-277, Jan. 1995.
    • (1995) IEEE Trans. Neural Netw , vol.6 , Issue.1 , pp. 273-277
    • Setiono, R.1    Hui, L.C.K.2
  • 19
    • 0031236099 scopus 로고    scopus 로고
    • Objective functions for training new hidden units in constructive neural networks
    • Sep
    • T.Y. Kwok and D. Y. Yeung, "Objective functions for training new hidden units in constructive neural networks," IEEE Trans. Neural Netw., vol. 8, no. 5, pp. 1131-1148, Sep. 1997.
    • (1997) IEEE Trans. Neural Netw , vol.8 , Issue.5 , pp. 1131-1148
    • Kwok, T.Y.1    Yeung, D.Y.2
  • 20
    • 0033097130 scopus 로고    scopus 로고
    • Fast initialization for cascade-correlation learning
    • Mar
    • M. Lehtokangas, "Fast initialization for cascade-correlation learning," IEEE Trans. Neural Netw., vol. 10, no. 2, pp. 410-414, Mar. 1999.
    • (1999) IEEE Trans. Neural Netw , vol.10 , Issue.2 , pp. 410-414
    • Lehtokangas, M.1
  • 21
    • 0034187293 scopus 로고    scopus 로고
    • Modified cascade-correlation learning for classification
    • May
    • M. Lehtokangas, "Modified cascade-correlation learning for classification," IEEE Trans. Neural Netw., vol. 11, no. 3, pp. 795-798, May 2000.
    • (2000) IEEE Trans. Neural Netw , vol.11 , Issue.3 , pp. 795-798
    • Lehtokangas, M.1
  • 22
    • 0036964229 scopus 로고    scopus 로고
    • A constructive algorithm for feedforward neural networks with incremental training
    • Dec
    • D. Liu, T.-S. Chang, and Y. Zhang, "A constructive algorithm for feedforward neural networks with incremental training," IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., vol. 49, no. 12, pp. 1876-1879, Dec. 2002.
    • (2002) IEEE Trans. Circuits Syst. I, Fundam. Theory Appl , vol.49 , Issue.12 , pp. 1876-1879
    • Liu, D.1    Chang, T.-S.2    Zhang, Y.3
  • 23
    • 23044516364 scopus 로고    scopus 로고
    • Constructive feedforward neural networks using Hermite polynomial activation functions
    • Jul
    • L. Ma and K. Khorasani, "Constructive feedforward neural networks using Hermite polynomial activation functions," IEEE Trans. Neural Netw. vol. 16, no. 4, pp. 821-833, Jul. 2005.
    • (2005) IEEE Trans. Neural Netw , vol.16 , Issue.4 , pp. 821-833
    • Ma, L.1    Khorasani, K.2
  • 24
    • 0000494466 scopus 로고
    • Optimal brain damage
    • D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann
    • Y. Le Cun, J. S. Denker, and S. A. Solla, "Optimal brain damage," in Proc. Advances Neural Inform. Process. Syst., D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990, vol. 2, pp. 598-605.
    • (1990) Proc. Advances Neural Inform. Process. Syst , vol.2 , pp. 598-605
    • Le Cun, Y.1    Denker, J.S.2    Solla, S.A.3
  • 25
    • 0001234705 scopus 로고
    • Second-order derivatives for network pruning: Optimal brain surgeon
    • C. Lee, S. Hanson, and J. Cowan, Eds. San Mateo, CA: Morgan Kaufmann
    • B. Hassibi and D. G. Stork, "Second-order derivatives for network pruning: Optimal brain surgeon," in Proc. Advances Neural Inform. Process. Syst., C. Lee, S. Hanson, and J. Cowan, Eds. San Mateo, CA: Morgan Kaufmann, 1993, vol. 5, pp. 164-171.
    • (1993) Proc. Advances Neural Inform. Process. Syst , vol.5 , pp. 164-171
    • Hassibi, B.1    Stork, D.G.2
  • 26
    • 0035505658 scopus 로고    scopus 로고
    • A new pruning heuristic based on variance analysis of sensitivity information
    • Nov
    • A. P. Engelbrecht, "A new pruning heuristic based on variance analysis of sensitivity information," IEEE Trans. Neural Netw., vol. 12, no. 6, pp. 1386-1399, Nov. 2001.
    • (2001) IEEE Trans. Neural Netw , vol.12 , Issue.6 , pp. 1386-1399
    • Engelbrecht, A.P.1
  • 27
    • 0025964567 scopus 로고
    • Back-propagation algorithm which varies the number of hidden units
    • Y. Hirose, K. Yamashita, and S. Hijiya, "Back-propagation algorithm which varies the number of hidden units," Neural Netw., vol. 4, no. 1, pp. 61-66, 1991.
    • (1991) Neural Netw , vol.4 , Issue.1 , pp. 61-66
    • Hirose, Y.1    Yamashita, K.2    Hijiya, S.3
  • 28
    • 0033712529 scopus 로고    scopus 로고
    • An algorithm for automatic design of two hidden layered artificial neural networks
    • Md. M. Islam and K. Murase, "An algorithm for automatic design of two hidden layered artificial neural networks," in Proc. IJCNN, 2000, pp. 467-472.
    • (2000) Proc. IJCNN , pp. 467-472
    • Islam, M.M.1    Murase, K.2
  • 29
    • 0034811555 scopus 로고    scopus 로고
    • A new algorithm to design compact two-hidden-layer artificial neural networks
    • Nov
    • Md. M. Islam and K. Murase, "A new algorithm to design compact two-hidden-layer artificial neural networks," Neural Netw., vol. 14, no. 9, pp. 1265-1278, Nov. 2001.
    • (2001) Neural Netw , vol.14 , Issue.9 , pp. 1265-1278
    • Islam, M.M.1    Murase, K.2
  • 30
    • 0042525842 scopus 로고    scopus 로고
    • Neural-network construction and selection in nonlinear modeling
    • Jul
    • I. Rivals and L. Personnaz, "Neural-network construction and selection in nonlinear modeling," IEEE Trans. Neural Netw., vol. 14, no. 4, pp. 804-819, Jul. 2003.
    • (2003) IEEE Trans. Neural Netw , vol.14 , Issue.4 , pp. 804-819
    • Rivals, I.1    Personnaz, L.2
  • 31
    • 0024137490 scopus 로고
    • Increased rates of convergence through learning rate adaptation
    • R. A. Jacobs, "Increased rates of convergence through learning rate adaptation," Neural Netw., vol. 1, no. 4, pp. 295-307, 1988.
    • (1988) Neural Netw , vol.1 , Issue.4 , pp. 295-307
    • Jacobs, R.A.1
  • 32
    • 85025505893 scopus 로고
    • Generalization performance of overtrained backpropagation networks
    • Y. Chauvin, "Generalization performance of overtrained backpropagation networks," in Proc. EUROSZP Workshop, 1990, pp. 46-55.
    • (1990) Proc. EUROSZP Workshop , pp. 46-55
    • Chauvin, Y.1
  • 33
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, M. Stinchcombe, and H. White, "Multilayer feedforward networks are universal approximators," Neural Netw., vol. 2, no. 5, pp. 359-366, 1989.
    • (1989) Neural Netw , vol.2 , Issue.5 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 34
    • 0025751820 scopus 로고
    • Approximation capabilities of multilayer feedforward networks
    • K. Hornik, "Approximation capabilities of multilayer feedforward networks," Neural Netw., vol. 4, no. 2, pp. 251-257, 1991.
    • (1991) Neural Netw , vol.4 , Issue.2 , pp. 251-257
    • Hornik, K.1
  • 35
    • 0000106040 scopus 로고
    • Universal approximation using radial basis function networks
    • J. Park and I. W. Sandberg, "Universal approximation using radial basis function networks," Neural Comput., vol. 3, no. 2, pp. 246-257, 1991.
    • (1991) Neural Comput , vol.3 , Issue.2 , pp. 246-257
    • Park, J.1    Sandberg, I.W.2
  • 36
    • 0027812765 scopus 로고
    • Some new results on neural-network approximation
    • K. Hornik, "Some new results on neural-network approximation," Neural Netw., vol. 6, pp. 1069-1072, 1993.
    • (1993) Neural Netw , vol.6 , pp. 1069-1072
    • Hornik, K.1
  • 37
    • 0001002401 scopus 로고
    • Approximation and radial-basis-function networks
    • Mar
    • J. Park and I. W. Sandberg, "Approximation and radial-basis-function networks," Neural Comput., vol. 5, no. 2, pp. 305-316, Mar. 1993.
    • (1993) Neural Comput , vol.5 , Issue.2 , pp. 305-316
    • Park, J.1    Sandberg, I.W.2
  • 38
    • 85033056841 scopus 로고
    • Combinations of genetic algorithms and neural networks: A survey of the state of the art
    • D. Whitley and J. D. Schaffer, Eds
    • J. D. Schaffer, D. Whitley, and L. J. Eshelman, "Combinations of genetic algorithms and neural networks: A survey of the state of the art," in Proc. Int. Workshop COGANN, D. Whitley and J. D. Schaffer, Eds., 1992, pp. 1-37.
    • (1992) Proc. Int. Workshop COGANN , pp. 1-37
    • Schaffer, J.D.1    Whitley, D.2    Eshelman, L.J.3
  • 39
    • 0027574256 scopus 로고
    • A review of evolutionary artificial neural networks
    • X. Yao, "A review of evolutionary artificial neural networks," Int. J. Intell. Syst., vol. 8, no. 4, pp. 539-567, 1993.
    • (1993) Int. J. Intell. Syst , vol.8 , Issue.4 , pp. 539-567
    • Yao, X.1
  • 40
    • 0033362601 scopus 로고    scopus 로고
    • Evolving artificial neural networks
    • Sep
    • X. Yao, "Evolving artificial neural networks," Proc. IEEE, vol. 87, no. 9, pp. 1423-1447, Sep. 1999.
    • (1999) Proc. IEEE , vol.87 , Issue.9 , pp. 1423-1447
    • Yao, X.1
  • 41
    • 84945797434 scopus 로고
    • Dynamic node creation in backpropagation networks
    • T. Ash, "Dynamic node creation in backpropagation networks," Connect. Sci., vol. 1, no. 4, pp. 365-375, 1989.
    • (1989) Connect. Sci , vol.1 , Issue.4 , pp. 365-375
    • Ash, T.1
  • 42
    • 0002551093 scopus 로고
    • Node splitting: A constructive algorithm for feedforward neural networks
    • Mar
    • M. Wynne-Jones, "Node splitting: A constructive algorithm for feedforward neural networks," Neural Comput. Appl., vol. 1, no. 1, pp. 17-22, Mar. 1993.
    • (1993) Neural Comput. Appl , vol.1 , Issue.1 , pp. 17-22
    • Wynne-Jones, M.1
  • 43
    • 0028255785 scopus 로고
    • Toward generating neural network structures for function approximation
    • T. M. Nabhan and A. Y. Zomaya, "Toward generating neural network structures for function approximation," Neural Netw., vol. 7, no. 1, pp. 89-99, 1994.
    • (1994) Neural Netw , vol.7 , Issue.1 , pp. 89-99
    • Nabhan, T.M.1    Zomaya, A.Y.2
  • 44
    • 0032207884 scopus 로고    scopus 로고
    • CARVE - A constructive algorithm for real-valued examples
    • Nov
    • S. Young and T. Downs, "CARVE - A constructive algorithm for real-valued examples," IEEE Trans. Neural Netw., vol. 9, no. 6, pp. 1180-1190, Nov. 1998.
    • (1998) IEEE Trans. Neural Netw , vol.9 , Issue.6 , pp. 1180-1190
    • Young, S.1    Downs, T.2
  • 46
    • 54249119198 scopus 로고    scopus 로고
    • A new constructive algorithm for designing and training artificial neural networks
    • Kitakyushu, Japan, Nov. 13-16
    • Md. A. Sattar, Md. M. Islam, and K. Murase, "A new constructive algorithm for designing and training artificial neural networks," in Proc. 14th ICONIP, Kitakyushu, Japan, Nov. 13-16, 2007, pp. 317-327.
    • (2007) Proc. 14th ICONIP , pp. 317-327
    • Sattar, M.A.1    Islam, M.M.2    Murase, K.3
  • 47
    • 56349135998 scopus 로고    scopus 로고
    • An adaptive merging and growing algorithm for designing artificial neural networks
    • Hong Kong, Jun. 1-8
    • Md. M. Islam, Md. F. Amin, S. Ahmmed, and K. Murase, "An adaptive merging and growing algorithm for designing artificial neural networks," in Proc. Int. Joint Conf. Neural Netw., Hong Kong, Jun. 1-8, 2008, pp. 2004-2009.
    • (2008) Proc. Int. Joint Conf. Neural Netw , pp. 2004-2009
    • Islam, M.M.1    Amin, M.F.2    Ahmmed, S.3    Murase, K.4
  • 48
    • 0003257214 scopus 로고
    • Prediction risk and architecture selection for neural in networks
    • V. Cherkassky, J. H. Friedman, and H. Wechsler, Eds. New York: Springer-Verlag
    • J. E. Moody, "Prediction risk and architecture selection for neural in networks," From Statistics to Neural Networks: Theory and Pattern Recognition Applications, V. Cherkassky, J. H. Friedman, and H. Wechsler, Eds. New York: Springer-Verlag, 1993, pp. 147-165.
    • (1993) From Statistics to Neural Networks: Theory and Pattern Recognition Applications , pp. 147-165
    • Moody, J.E.1
  • 49
    • 0003380928 scopus 로고
    • Temporal processing with recurrent networks: An evolutionary approach
    • R. K. Belew and L. B. Booker, Eds
    • J. Torreele, "Temporal processing with recurrent networks: An evolutionary approach,"in Proc. 4th Int. Conf. Genetic Algorithms R. K. Belew and L. B. Booker, Eds., 1991, pp. 555-561.
    • (1991) Proc. 4th Int. Conf. Genetic Algorithms , pp. 555-561
    • Torreele, J.1
  • 50
    • 0029548090 scopus 로고
    • Evolving recurrent neural networks with non-binary encoding
    • Part 2of 2
    • M. Mandischer, "Evolving recurrent neural networks with non-binary encoding," in Proc. IEEE Int. Conf. Evol. Comput., 1995, pp. 584-589. Part 2(of 2).
    • (1995) Proc. IEEE Int. Conf. Evol. Comput , pp. 584-589
    • Mandischer, M.1
  • 51
    • 0031375741 scopus 로고    scopus 로고
    • F. Heimes, G. Zalesski, W. Land, Jr., and M. Oshima, Traditional and evolved dynamic neural networks for aircraft simulation, in Proc. IEEE Int. Conf. Syst., Men, Cybern., 1997, pp. 1995-2000. Part 3(of 5).
    • F. Heimes, G. Zalesski, W. Land, Jr., and M. Oshima, "Traditional and evolved dynamic neural networks for aircraft simulation," in Proc. IEEE Int. Conf. Syst., Men, Cybern., 1997, pp. 1995-2000. Part 3(of 5).
  • 52
    • 0025477595 scopus 로고
    • Genetic algorithms and neural networks: Optimizing connections and connectivity
    • Aug
    • D. Whitley, T. Starkweather, and C. Bogart, "Genetic algorithms and neural networks: Optimizing connections and connectivity," Perallel Comput., vol. 14, no. 3, pp. 347-361, Aug. 1990.
    • (1990) Perallel Comput , vol.14 , Issue.3 , pp. 347-361
    • Whitley, D.1    Starkweather, T.2    Bogart, C.3
  • 53
    • 0005021990 scopus 로고
    • Optimizing small neural networks using a distributed genetic algorithm
    • Hillsdale, NJ: Lawrence Erlbaum
    • D. Whitley and T. Starkweather, "Optimizing small neural networks using a distributed genetic algorithm," in Proc. Int. Joint Conf. Neural Netw. Hillsdale, NJ: Lawrence Erlbaum, 1990, vol. I, pp. 206-209.
    • (1990) Proc. Int. Joint Conf. Neural Netw , vol.1 , pp. 206-209
    • Whitley, D.1    Starkweather, T.2
  • 54
    • 0000680827 scopus 로고
    • A preliminary study on designing artificial neural networks using co-evolution
    • Singapore, Jun
    • X. Yao and Y. Shi, "A preliminary study on designing artificial neural networks using co-evolution," in Proc. IEEE Singapore Int. Conf. Intell. Control Instrum., Singapore, Jun. 1995, pp. 149-154.
    • (1995) Proc. IEEE Singapore Int. Conf. Intell. Control Instrum , pp. 149-154
    • Yao, X.1    Shi, Y.2
  • 55
    • 0001793307 scopus 로고
    • The evolution of learning: An experiment in genetic connectionism
    • D. S. Touretzky, J. L. Elman, and G. E. Hinton, Eds
    • D. J. Chalmers, "The evolution of learning: An experiment in genetic connectionism," in Proc. Connectionist Models Summer School, D. S. Touretzky, J. L. Elman, and G. E. Hinton, Eds., 1990, pp. 81-90.
    • (1990) Proc. Connectionist Models Summer School , pp. 81-90
    • Chalmers, D.J.1
  • 56
    • 67349149937 scopus 로고    scopus 로고
    • Y. Bengio and S. Bengio, Learning a synaptic learning role, in Dét. Informatique et de Recherche Operationelle, Univ. Montreal, Montreal, QC, Canada, Tech. Rep. 751, Nov. 1990.
    • Y. Bengio and S. Bengio, "Learning a synaptic learning role," in "Dét. Informatique et de Recherche Operationelle," Univ. Montreal, Montreal, QC, Canada, Tech. Rep. 751, Nov. 1990.
  • 57
    • 0040892464 scopus 로고
    • Evolving a learning algorithm for the binary perceptron
    • Nov
    • J. F. Fontanari and R. Meir, "Evolving a learning algorithm for the binary perceptron," Network, vol. 2, no. 4, pp. 353-359, Nov. 1991.
    • (1991) Network , vol.2 , Issue.4 , pp. 353-359
    • Fontanari, J.F.1    Meir, R.2
  • 58
    • 0026624310 scopus 로고
    • Genetic generation of both the weights and architecture for a neural network
    • Seattle, WA
    • J. R. Koza and J. P. Rice, "Genetic generation of both the weights and architecture for a neural network," in Proc. IEEE IJCNN, Seattle, WA, 1991, vol. 2, pp. 397-404.
    • (1991) Proc. IEEE IJCNN , vol.2 , pp. 397-404
    • Koza, J.R.1    Rice, J.P.2
  • 59
    • 0026711747 scopus 로고
    • General asymmetric neural networks and structure design by genetic algorithms
    • S. Bornholdt and D. Graudenz, "General asymmetric neural networks and structure design by genetic algorithms," Neural Netw., vol. 5, no. 2, pp. 327-334, 1992.
    • (1992) Neural Netw , vol.5 , Issue.2 , pp. 327-334
    • Bornholdt, S.1    Graudenz, D.2
  • 60
    • 0000877308 scopus 로고
    • A distributed genetic algorithm for neural network design and training
    • S. Oliker, M. Furst, and O. Maimon, "A distributed genetic algorithm for neural network design and training," Complex Syst., vol. 6, pp. 459-477, 1992.
    • (1992) Complex Syst , vol.6 , pp. 459-477
    • Oliker, S.1    Furst, M.2    Maimon, O.3
  • 61
    • 0031143030 scopus 로고    scopus 로고
    • A new evolutionary system for evolving artificial neural networks
    • May
    • X. Yao and Y. Liu, "A new evolutionary system for evolving artificial neural networks," IEEE Trans. Neural Netw., vol. 8, no. 3, pp. 694-713, May 1997.
    • (1997) IEEE Trans. Neural Netw , vol.8 , Issue.3 , pp. 694-713
    • Yao, X.1    Liu, Y.2
  • 62
    • 37249025207 scopus 로고    scopus 로고
    • Graph matching recombination for evolving neural networks
    • Nanjing, China, Jun. 3-7
    • A. Mahmood, S. Sharmin, D. Barua, and Md. M. Islam, "Graph matching recombination for evolving neural networks," in Proc. 4th Int. Symp. Neural Netw., Nanjing, China, Jun. 3-7, 2007, pp. 562-568.
    • (2007) Proc. 4th Int. Symp. Neural Netw , pp. 562-568
    • Mahmood, A.1    Sharmin, S.2    Barua, D.3    Islam, M.M.4
  • 63
    • 0001927486 scopus 로고
    • Temporal evolution of generalization during learning in linear networks
    • P. Baldi and Y. Chauvin, "Temporal evolution of generalization during learning in linear networks," Neural Comput., vol. 3, no. 4, pp. 589-603, 1991.
    • (1991) Neural Comput , vol.3 , Issue.4 , pp. 589-603
    • Baldi, P.1    Chauvin, Y.2
  • 64
    • 0035444457 scopus 로고    scopus 로고
    • A new crossover operator and its application to artificial neural networks evolution
    • Md. M. Islam and K. Murase, "A new crossover operator and its application to artificial neural networks evolution," IEICE Trans. Inf. Syst., vol. E84-D, no. 9, pp. 1144-1154, 2001.
    • (2001) IEICE Trans. Inf. Syst , vol.E84-D , Issue.9 , pp. 1144-1154
    • Islam, M.M.1    Murase, K.2
  • 65
    • 0000155950 scopus 로고
    • The cascade-correlation learning architecture
    • D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann
    • S. E. Fahlman and C. Lebiere, "The cascade-correlation learning architecture," in Proc. Advences Neural Inform. Process. Syst., D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990, vol. 2, pp. 524-532.
    • (1990) Proc. Advences Neural Inform. Process. Syst , vol.2 , pp. 524-532
    • Fahlman, S.E.1    Lebiere, C.2
  • 69
    • 0042525838 scopus 로고    scopus 로고
    • A constructive algorithm for training cooperative neural network ensembles
    • Jul
    • Md. M. Islam, X. Yao, and K. Murase, "A constructive algorithm for training cooperative neural network ensembles," IEEE Trans. Neural Netw., vol. 14, no. 4, pp. 820-834, Jul. 2003.
    • (2003) IEEE Trans. Neural Netw , vol.14 , Issue.4 , pp. 820-834
    • Islam, M.M.1    Yao, X.2    Murase, K.3
  • 70
    • 0027149401 scopus 로고
    • Evolutional development of a multilevel neural network
    • S. V. Odri, D. P. Petrovacki, and G. A. Krstonosic, "Evolutional development of a multilevel neural network," Neural Netw., vol. 6, no. 4, pp. 583-595, 1993.
    • (1993) Neural Netw , vol.6 , Issue.4 , pp. 583-595
    • Odri, S.V.1    Petrovacki, D.P.2    Krstonosic, G.A.3
  • 71
    • 0032099978 scopus 로고    scopus 로고
    • Automatic early stopping using cross validation: Quantifying the criteria
    • Jun
    • L. Prechelt, "Automatic early stopping using cross validation: Quantifying the criteria," Neural Netw., vol. 11, no. 4, pp. 761-767, Jun. 1998.
    • (1998) Neural Netw , vol.11 , Issue.4 , pp. 761-767
    • Prechelt, L.1
  • 72
    • 0029412003 scopus 로고
    • Some notes on neural learning algorithm benchmarking
    • Dec
    • L. Prechelt, "Some notes on neural learning algorithm benchmarking," Neurocomputing, vol. 9, no. 3, pp. 343-347, Dec. 1995.
    • (1995) Neurocomputing , vol.9 , Issue.3 , pp. 343-347
    • Prechelt, L.1
  • 73
    • 0030130727 scopus 로고    scopus 로고
    • A quantitative study of experimental evaluations of neural network learning algorithms
    • Apr
    • L. Prechelt, "A quantitative study of experimental evaluations of neural network learning algorithms," Neural Netw., vol. 9, no. 3, pp. 457-462, Apr. 1996.
    • (1996) Neural Netw , vol.9 , Issue.3 , pp. 457-462
    • Prechelt, L.1
  • 74
    • 34848872651 scopus 로고    scopus 로고
    • An optimization methodology for neural network weights and architectures
    • Nov
    • T. B. Ludermir, A. Yamazaki, and C. Zanchettin, "An optimization methodology for neural network weights and architectures," IEEE Trans. Neural Netw., vol. 17, no. 6, pp. 1452-1459, Nov. 2006.
    • (2006) IEEE Trans. Neural Netw , vol.17 , Issue.6 , pp. 1452-1459
    • Ludermir, T.B.1    Yamazaki, A.2    Zanchettin, C.3
  • 75
    • 26444479778 scopus 로고
    • Optimization by simulated annealing
    • May
    • S. Kirkpatrick, C. D. Gelatt, Jr., and M. P. Vecchi, "Optimization by simulated annealing," Science, vol. 220, no. 4598, pp. 671-680, May 1983.
    • (1983) Science , vol.220 , Issue.4598 , pp. 671-680
    • Kirkpatrick, S.1    Gelatt Jr., C.D.2    Vecchi, M.P.3
  • 76
    • 0022865373 scopus 로고
    • Future paths for integer programming and links to artificial intelligence
    • May
    • F. Glover, "Future paths for integer programming and links to artificial intelligence," Comput. Oper. Res., vol. 13, no. 5, pp. 533-549, May 1986.
    • (1986) Comput. Oper. Res , vol.13 , Issue.5 , pp. 533-549
    • Glover, F.1
  • 77
    • 0342990011 scopus 로고    scopus 로고
    • An analysis of noise in recurrent neural networks: Convergence and generalization
    • Nov
    • K. Jim, C. L. Giles, and B. G. Horne, "An analysis of noise in recurrent neural networks: Convergence and generalization," IEEE Trans. Neural Netw., vol. 7, no. 6, pp. 1424-1438, Nov. 1996.
    • (1996) IEEE Trans. Neural Netw , vol.7 , Issue.6 , pp. 1424-1438
    • Jim, K.1    Giles, C.L.2    Horne, B.G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.