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Volumn 10, Issue 3, 2001, Pages 214-230

A robust evolutionary algorithm for training neural networks

Author keywords

Adaptive mutations; Evolutionary algorithm; Family competition; Multiple mutations; Neural networks

Indexed keywords


EID: 0035566378     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s521-001-8050-2     Document Type: Article
Times cited : (44)

References (33)
  • 1
    • 0025751820 scopus 로고
    • Approximation capabilities of multilayer feedforward networks
    • Hornik K. Approximation capabilities of multilayer feedforward networks. Neural Networks 1991; 4: 251-257
    • (1991) Neural Networks , vol.4 , pp. 251-257
    • Hornik, K.1
  • 4
    • 0030108039 scopus 로고    scopus 로고
    • The cascade-correlation learning: A projection pursuit learning perspective
    • Hwang J-N, You S-S, Lay S-R, Jou I-C. The cascade-correlation learning: A projection pursuit learning perspective. IEEE Trans Neural Networks 1996; 7(2): 278-289
    • (1996) IEEE Trans Neural Networks , vol.7 , Issue.2 , pp. 278-289
    • Hwang, J.-N.1    You, S.-S.2    Lay, S.-R.3    Jou, I.-C.4
  • 6
    • 0028392483 scopus 로고
    • Learning long-term dependencies with gradient descent is difficult
    • Bengio Y, Simard P, Frasconi P. Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Networks 1994; 5(2): 157-166
    • (1994) IEEE Trans Neural Networks , vol.5 , Issue.2 , pp. 157-166
    • Bengio, Y.1    Simard, P.2    Frasconi, P.3
  • 10
    • 11844285519 scopus 로고
    • Epistasis variance: Suitability of a representation to genetic algorithms
    • Davidor Y. Epistasis variance: Suitability of a representation to genetic algorithms. Complex Systems 1990; 4: 368-383
    • (1990) Complex Systems , vol.4 , pp. 368-383
    • Davidor, Y.1
  • 11
    • 0000308566 scopus 로고
    • Real-coded genetic algorithms and interval-schemata
    • LD Whitley, editor, Morgan Kaufmann
    • Eshelman LJ, Schaffer JD. Real-coded genetic algorithms and interval-schemata. In: LD Whitley, editor, Foundation of Genetic Algorithms 2. Morgan Kaufmann, 1993; 187-202
    • (1993) Foundation of Genetic Algorithms 2 , pp. 187-202
    • Eshelman, L.J.1    Schaffer, J.D.2
  • 12
    • 0003140039 scopus 로고
    • Predictive models for the breeder genetic algorithm I. Continuous parameters optimisation
    • Mühlenbein H, Schlierkamp-Voosen D. Predictive models for the breeder genetic algorithm I. Continuous parameters optimisation. Evolutionary Computation 1993; 1(1): 24-49
    • (1993) Evolutionary Computation , vol.1 , Issue.1 , pp. 24-49
    • Mühlenbein, H.1    Schlierkamp-Voosen, D.2
  • 13
    • 0002640807 scopus 로고    scopus 로고
    • Integrating adaptive mutations and family competition into genetic algorithms as function optimizer
    • Yang J-M, Kao C-Y. Integrating adaptive mutations and family competition into genetic algorithms as function optimizer. Soft Computing 2000; 4(2): 89-102
    • (2000) Soft Computing , vol.4 , Issue.2 , pp. 89-102
    • Yang, J.-M.1    Kao, C.-Y.2
  • 15
    • 84982464075 scopus 로고
    • Empirical studies on the speed of the convergence of neural network training using genetic algorithms
    • Kitano H. Empirical studies on the speed of the convergence of neural network training using genetic algorithms. Proc Int Conf on Artificial Intelligence 1990; 789-795
    • (1990) Proc Int Conf on Artificial Intelligence , pp. 789-795
    • Kitano, H.1
  • 18
    • 21744438068 scopus 로고    scopus 로고
    • Applying family competition to evolution strategies for constrained optimisation
    • Angeline PJ, Reynolds RG, McDonnell JR, Eberhart R, editors
    • Yang J-M, Chen Y-P, Horng J-T, Kao C-Y. Applying family competition to evolution strategies for constrained optimisation. In: Angeline PJ, Reynolds RG, McDonnell JR, Eberhart R, editors, Lecture Notes in Computer Science 1213. 1997; 201-211
    • (1997) Lecture Notes in Computer Science , vol.1213 , pp. 201-211
    • Yang, J.-M.1    Chen, Y.-P.2    Horng, J.-T.3    Kao, C.-Y.4
  • 20
    • 0002651837 scopus 로고
    • An overview of evolution algorithms for parameter optimisation
    • Bäck T, Schwefel H-P. An overview of evolution algorithms for parameter optimisation. Evolutionary Computation 1993; 1(1): 1-23
    • (1993) Evolutionary Computation , vol.1 , Issue.1 , pp. 1-23
    • Bäck, T.1    Schwefel, H.-P.2
  • 22
    • 0031277292 scopus 로고    scopus 로고
    • Local convergence rates of simple evolutionary algorithms with cauchy mutations
    • Rudolph G. Local convergence rates of simple evolutionary algorithms with cauchy mutations. IEEE Trans Evolutionary Computation 1997; 1(4): 249-258
    • (1997) IEEE Trans Evolutionary Computation , vol.1 , Issue.4 , pp. 249-258
    • Rudolph, G.1
  • 23
    • 0025477595 scopus 로고
    • Genetic algorithms and neural networks: Optimizing connections and connectivity
    • Whitley D, Starkweather T, Bogart C. Genetic algorithms and neural networks: Optimizing connections and connectivity. Parallel Computing 1990; 14: 347-361
    • (1990) Parallel Computing , vol.14 , pp. 347-361
    • Whitley, D.1    Starkweather, T.2    Bogart, C.3
  • 25
  • 27
    • 0029769829 scopus 로고    scopus 로고
    • The pandemonium system of reflective agents
    • Smieja F. The pandemonium system of reflective agents. IEEE Trans Neural Networks 1996; 7(1): 97-106
    • (1996) IEEE Trans Neural Networks , vol.7 , Issue.1 , pp. 97-106
    • Smieja, F.1
  • 29
    • 0002855385 scopus 로고
    • Scaling relationships in backpropagation learning
    • Tesauro G, Janssens B. Scaling relationships in backpropagation learning. Complex Systems 1988; 2: 39-84
    • (1988) Complex Systems , vol.2 , pp. 39-84
    • Tesauro, G.1    Janssens, B.2
  • 30
    • 19544362505 scopus 로고    scopus 로고
    • A new evolutionary system for evolving artificial neural networks
    • Yao X, Liu Y. A new evolutionary system for evolving artificial neural networks. IEEE Trans Neural Networks 1996
    • (1996) IEEE Trans Neural Networks
    • Yao, X.1    Liu, Y.2
  • 31
    • 0023843391 scopus 로고
    • Analysis of hidden units in a layered network trained to classify sonar targets
    • Gorman RP, Sejnowski TJ. Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks 1988; 1: 75-89
    • (1988) Neural Networks , vol.1 , pp. 75-89
    • Gorman, R.P.1    Sejnowski, T.J.2
  • 32
    • 0030270953 scopus 로고    scopus 로고
    • Grail: A multi-agent neural network system for gene identification
    • Xu Y, Mural RJ, Einstein JR, Shah MB, Uberbacher EC. Grail: A multi-agent neural network system for gene identification. Proc IEEE 1996; 84(10): 1544-1552
    • (1996) Proc IEEE , vol.84 , Issue.10 , pp. 1544-1552
    • Xu, Y.1    Mural, R.J.2    Einstein, J.R.3    Shah, M.B.4    Uberbacher, E.C.5
  • 33
    • 0000873042 scopus 로고    scopus 로고
    • Flexible ligand docking using a robust evolutionary algorithm
    • Yang J-M, Kao C-Y. Flexible ligand docking using a robust evolutionary algorithm. J Computational Chemistry 2000; 21(11): 988-998
    • (2000) J Computational Chemistry , vol.21 , Issue.11 , pp. 988-998
    • Yang, J.-M.1    Kao, C.-Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.