메뉴 건너뛰기




Volumn 72, Issue 4-6, 2009, Pages 1198-1204

Selective combination of multiple neural networks for improving model prediction in nonlinear systems modelling through forward selection and backward elimination

Author keywords

Backward elimination; Forward selection; Generalisation; Multiple neural networks; Selective combination of neural networks

Indexed keywords

BACKWARD ELIMINATION; FORWARD SELECTION; GENERALISATION; MULTIPLE NEURAL NETWORKS; SELECTIVE COMBINATION OF NEURAL NETWORKS;

EID: 58149472217     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.02.005     Document Type: Article
Times cited : (26)

References (30)
  • 2
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Brieman L. Bagging predictors. Mach. Learn. 24 (1996) 123-140
    • (1996) Mach. Learn. , vol.24 , pp. 123-140
    • Brieman, L.1
  • 3
    • 0000782329 scopus 로고    scopus 로고
    • Overfitting in neural networks: backpropagation, conjugate gradient and early stopping
    • Caruana R., Lawrence S., and Giles C.L. Overfitting in neural networks: backpropagation, conjugate gradient and early stopping. Neural Inf. Process. System 13 (2000) 402-408
    • (2000) Neural Inf. Process. System , vol.13 , pp. 402-408
    • Caruana, R.1    Lawrence, S.2    Giles, C.L.3
  • 4
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization
    • Dietterich T.G. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Mach. Learn. 40 (2000) 139-157
    • (2000) Mach. Learn. , vol.40 , pp. 139-157
    • Dietterich, T.G.1
  • 6
    • 0034243832 scopus 로고    scopus 로고
    • Bootstrapping neural networks
    • Franke J., and Neumann M.H. Bootstrapping neural networks. Neural Comput. 12 (2000) 1929-1949
    • (2000) Neural Comput. , vol.12 , pp. 1929-1949
    • Franke, J.1    Neumann, M.H.2
  • 7
    • 0033720244 scopus 로고    scopus 로고
    • K. Hagiwara, K. Kuno, Regularisation learning and early stopping in linear networks, in: International Joint Conference on Neural Networks, 2000, pp. 511-516.
    • K. Hagiwara, K. Kuno, Regularisation learning and early stopping in linear networks, in: International Joint Conference on Neural Networks, 2000, pp. 511-516.
  • 8
    • 0031171679 scopus 로고    scopus 로고
    • Optimal linear combination
    • Hashem S. Optimal linear combination. Neural Networks 10 (1997) 599-614
    • (1997) Neural Networks , vol.10 , pp. 599-614
    • Hashem, S.1
  • 9
    • 0003283733 scopus 로고    scopus 로고
    • Treating harmful collinearity in neural networks ensembles
    • Sharkey A.J.C. (Ed), Springer Publication, London
    • Hashem S. Treating harmful collinearity in neural networks ensembles. In: Sharkey A.J.C. (Ed). Combining Artificial Neural Nets Ensemble and Modular (1999), Springer Publication, London
    • (1999) Combining Artificial Neural Nets Ensemble and Modular
    • Hashem, S.1
  • 12
    • 0000262562 scopus 로고
    • Hierarchical mixtures of expert and the EM algorithm
    • Jordan M.I., and Jacobs R.A. Hierarchical mixtures of expert and the EM algorithm. Neural Comput. 6 (1994) 191-214
    • (1994) Neural Comput. , vol.6 , pp. 191-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 14
    • 0034284315 scopus 로고    scopus 로고
    • Input selection based on an ensembles
    • Laar P.V.D. Input selection based on an ensembles. Neurocomputing 34 (2000) 227-238
    • (2000) Neurocomputing , vol.34 , pp. 227-238
    • Laar, P.V.D.1
  • 16
    • 0035100447 scopus 로고    scopus 로고
    • Improving neural networks training solution using regularization
    • McLoone S., and Irwin G. Improving neural networks training solution using regularization. Neurocomputing 37 (2001) 71-90
    • (2001) Neurocomputing , vol.37 , pp. 71-90
    • McLoone, S.1    Irwin, G.2
  • 17
    • 58149472447 scopus 로고    scopus 로고
    • N. Morgan, H. Bourlard, Generalisation and Parameter Estimation in Feedforward Nets: Some Experiments, San Mateo, CA, 1990.
    • N. Morgan, H. Bourlard, Generalisation and Parameter Estimation in Feedforward Nets: Some Experiments, San Mateo, CA, 1990.
  • 18
    • 0031644261 scopus 로고    scopus 로고
    • M. Ohbayashi, K. Hirasawa, K. Toshimitsu, J. Murata, J. Hu, Robust control for non-linear system by universal learning networks considering fuzzy criterion and second order derivatives, in: IEEE World Congress on Computational Intelligence: IEEE International Conference Proceedings on Neural Networks, vol. 2, 1998, pp. 968-973.
    • M. Ohbayashi, K. Hirasawa, K. Toshimitsu, J. Murata, J. Hu, Robust control for non-linear system by universal learning networks considering fuzzy criterion and second order derivatives, in: IEEE World Congress on Computational Intelligence: IEEE International Conference Proceedings on Neural Networks, vol. 2, 1998, pp. 968-973.
  • 19
    • 0000926506 scopus 로고
    • When networks disagree: ensemble methods for hybrid neural networks
    • Mammone R.J. (Ed), Chapman & Hall, London
    • Perrone M.P., and Cooper L.N. When networks disagree: ensemble methods for hybrid neural networks. In: Mammone R.J. (Ed). Artificial Neural Networks for Speech and Vision (1993), Chapman & Hall, London 126-142
    • (1993) Artificial Neural Networks for Speech and Vision , pp. 126-142
    • Perrone, M.P.1    Cooper, L.N.2
  • 21
    • 0001906968 scopus 로고    scopus 로고
    • Sharkey A.J.C. (Ed), Springer Publication, London
    • In: Sharkey A.J.C. (Ed). Multi Nets System (1999), Springer Publication, London
    • (1999) Multi Nets System
  • 22
    • 0030243055 scopus 로고    scopus 로고
    • Process modelling using stacked neural networks
    • Sridhar D.V., Bartlett E.B., and Seagrave R.C. Process modelling using stacked neural networks. AIChE J. 42 (1996) 2529-2539
    • (1996) AIChE J. , vol.42 , pp. 2529-2539
    • Sridhar, D.V.1    Bartlett, E.B.2    Seagrave, R.C.3
  • 23
    • 0032808458 scopus 로고    scopus 로고
    • An information theoretic approach for combining neural network process models
    • Sridhar D.V., Bartlett E.B., and Seagrave R.C. An information theoretic approach for combining neural network process models. Neural Networks 12 (1999) 915-926
    • (1999) Neural Networks , vol.12 , pp. 915-926
    • Sridhar, D.V.1    Bartlett, E.B.2    Seagrave, R.C.3
  • 24
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolpert D.H. Stacked generalization. Neural Networks 5 (1992) 241-259
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.H.1
  • 25
    • 0032928495 scopus 로고    scopus 로고
    • Developing robust non-linear models through bootstrap aggregated neural networks
    • Zhang J. Developing robust non-linear models through bootstrap aggregated neural networks. Neurocomputing 25 (1999) 93-113
    • (1999) Neurocomputing , vol.25 , pp. 93-113
    • Zhang, J.1
  • 26
    • 0032804290 scopus 로고    scopus 로고
    • Inferential estimation of polymer quality using bootstrap aggregated neural networks
    • Zhang J. Inferential estimation of polymer quality using bootstrap aggregated neural networks. Neural Networks 12 (1999) 927-938
    • (1999) Neural Networks , vol.12 , pp. 927-938
    • Zhang, J.1
  • 27
    • 0035165656 scopus 로고    scopus 로고
    • Developing robust neural network models by using both dynamic and static process operating data
    • Zhang J. Developing robust neural network models by using both dynamic and static process operating data. Ind. Eng. Chem. Res. 40 (2001) 234-241
    • (2001) Ind. Eng. Chem. Res. , vol.40 , pp. 234-241
    • Zhang, J.1
  • 28
    • 0031628183 scopus 로고    scopus 로고
    • Long-term prediction models based on mixed order locally recurrent neural networks
    • Zhang J., Morris A.J., and Martin E.B. Long-term prediction models based on mixed order locally recurrent neural networks. Comput. Chem. Eng. 22 (1998) 1051-1063
    • (1998) Comput. Chem. Eng. , vol.22 , pp. 1051-1063
    • Zhang, J.1    Morris, A.J.2    Martin, E.B.3
  • 29
    • 0032031419 scopus 로고    scopus 로고
    • Prediction of polymer quality in batch polymerisation reactors using robust neural networks
    • Zhang J., Morris A.J., Martin E.B., and Kiparissides C. Prediction of polymer quality in batch polymerisation reactors using robust neural networks. Chem. Eng. J. 69 (1998) 135-143
    • (1998) Chem. Eng. J. , vol.69 , pp. 135-143
    • Zhang, J.1    Morris, A.J.2    Martin, E.B.3    Kiparissides, C.4
  • 30
    • 0036567392 scopus 로고    scopus 로고
    • Ensembling neural networks: many could be better than all
    • Zhou Z.H., Wu J., and Tang W. Ensembling neural networks: many could be better than all. Artif. Intell. 137 1-2 (2002) 239
    • (2002) Artif. Intell. , vol.137 , Issue.1-2 , pp. 239
    • Zhou, Z.H.1    Wu, J.2    Tang, W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.