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Volumn 13, Issue 6, 2000, Pages 685-694

Methodology for building neural networks models from empirical engineering data

Author keywords

[No Author keywords available]

Indexed keywords

ERROR ANALYSIS; MATHEMATICAL MODELS;

EID: 0034509548     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0952-1976(00)00053-1     Document Type: Article
Times cited : (28)

References (21)
  • 1
    • 0033231649 scopus 로고    scopus 로고
    • Ensemble modeling or selecting the best model: many can be better than one
    • Barai, S.V., Reich, Y., 1999. Ensemble modeling or selecting the best model: many can be better than one. AI EDAM 13 (5), 377-386.
    • (1999) AI EDAM , vol.13 , Issue.5 , pp. 377-386
    • Barai, S.V.1    Reich, Y.2
  • 3
    • 0030344230 scopus 로고    scopus 로고
    • Heuristics of instability and stabilization
    • Breiman, L., 1996. Heuristics of instability and stabilization. The Annals of Statistics, 24 (6), 2350-2383.
    • (1996) The Annals of Statistics , vol.24 , Issue.6 , pp. 2350-2383
    • Breiman, L.1
  • 7
    • 0001942829 scopus 로고
    • Neural networks and the bias/variance dilemma
    • Geman, S., Bienstock, E., Doursat, R. 1992. Neural networks and the bias/variance dilemma. Neural Computation 4 (1), 1-58.
    • (1992) Neural Computation , vol.4 , Issue.1 , pp. 1-58
    • Geman, S.1    Bienstock, E.2    Doursat, R.3
  • 8
    • 85054435084 scopus 로고
    • Neural network ensembles, cross validation, and active learning
    • In: Tesauro, G., Touretzky, D.S., Leen, T.K. (Eds.), Cambridge, MA, MIT Press
    • Krogh, A., Vedelsby, J., 1995. Neural network ensembles, cross validation, and active learning. In: Tesauro, G., Touretzky, D.S., Leen, T.K. (Eds.), Advances in Neural Information Processing Systems, Vol. 7 Cambridge, MA, MIT Press, pp. 231-238.
    • (1995) Advances in Neural Information Processing Systems , vol.7 , pp. 231-238
    • Krogh, A.1    Vedelsby, J.2
  • 10
    • 0031188065 scopus 로고    scopus 로고
    • Machine learning techniques for civil engineering problems
    • Reich, Y., 1997. Machine learning techniques for civil engineering problems. Microcomputers in Civil Engineering 12 (4), 307-322.
    • (1997) Microcomputers in Civil Engineering , vol.12 , Issue.4 , pp. 307-322
    • Reich, Y.1
  • 12
    • 0032628293 scopus 로고    scopus 로고
    • Evaluating machine learning models for engineering problems
    • Reich, Y., Barai, S.V., 1999. Evaluating machine learning models for engineering problems. Artificial Intelligence in Engineering 13 (3), 257-272.
    • (1999) Artificial Intelligence in Engineering , vol.13 , Issue.3 , pp. 257-272
    • Reich, Y.1    Barai, S.V.2
  • 14
    • 0031193540 scopus 로고    scopus 로고
    • On topology, size and generalization of non-linear feed-forward neural networks
    • Rudolph, S., 1997. On topology, size and generalization of non-linear feed-forward neural networks. Neurocomputing 16 (1), 1-22.
    • (1997) Neurocomputing , vol.16 , Issue.1 , pp. 1-22
    • Rudolph, S.1
  • 16
    • 0345195977 scopus 로고    scopus 로고
    • Universal approximation using feedforward neurals networks: A survey of some existing methods, and some new results
    • Scarselli, F., Tsoi, A.C., 1998. Universal approximation using feedforward neurals networks: a survey of some existing methods, and some new results. Neural Networks 11 (1), 15-37.
    • (1998) Neural Networks , vol.11 , Issue.1 , pp. 15-37
    • Scarselli, F.1    Tsoi, A.C.2
  • 18
    • 0000684508 scopus 로고
    • Training neural networks with deficient data
    • In: Cowan, J.D., Tesauro, G., Alspector, J. (Eds.), Morgan Kaufmann, San Mateo
    • Tresp, V., Ahmad, S., Neuneier, R., 1994. Training neural networks with deficient data. In: Cowan, J.D., Tesauro, G., Alspector, J. (Eds.), Advances in Neural Information Processing Systems, Vol. 6 Morgan Kaufmann, San Mateo, pp. 128-135.
    • (1994) Advances in Neural Information Processing Systems , vol.6 , pp. 128-135
    • Tresp, V.1    Ahmad, S.2    Neuneier, R.3
  • 20
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolpert, D.H., 1992. Stacked generalization. Neural Networks. 5, 241-259.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.H.1
  • 21
    • 0009638722 scopus 로고
    • The relationship between PAC, the stastical physics framework, the Bayesian framework, and the VC framework
    • In: Wolpert, D.H. (Ed.), Addison-Wesley, Reading, MA.
    • Wolpert, D.H., 1995. The relationship between PAC, the stastical physics framework, the Bayesian framework, and the VC framework. In: Wolpert, D.H. (Ed.), Mathematics of Generalization. Addison-Wesley, Reading, MA.
    • (1995) Mathematics of Generalization
    • Wolpert, D.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.