메뉴 건너뛰기




Volumn 3, Issue 2, 2002, Pages 180-202

Modelling empirical data and decision making with neural networks

Author keywords

forecasting; linear models; Neural networks; regression based decision models

Indexed keywords


EID: 33745048103     PISSN: 14624621     EISSN: 17415187     Source Type: Journal    
DOI: 10.1504/IJMDM.2002.002472     Document Type: Article
Times cited : (6)

References (101)
  • 2
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik, M., Stinchcombe, M. and White, H. (1989) ‘Multilayer feedforward networks are universal approximators’, Neural Networks, Vol. 2, pp.359–366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, M.1    Stinchcombe, M.2    White, H.3
  • 3
    • 0002179750 scopus 로고
    • Neural networks
    • Wilson, L.R. and Sharda, R. (1992) ‘Neural networks’, OR/MS Today, August, pp.36–42.
    • (1992) OR/MS Today , vol.August , pp. 36-42
    • Wilson, L.R.1    Sharda, R.2
  • 4
    • 0039280062 scopus 로고
    • A neural network approach to stock market holding period returns
    • Wong, S.Q. and Long, J.A. (1995) ‘A neural network approach to stock market holding period returns’, American Business Review, Vol. 13, No. 2, pp.61–64.
    • (1995) American Business Review , vol.13 , Issue.2 , pp. 61-64
    • Wong, S.Q.1    Long, J.A.2
  • 5
    • 21344493313 scopus 로고
    • Neural networks for the MS/OR analyst: An application bibliography
    • Sharda, R. (1994) ‘Neural networks for the MS/OR analyst: An application bibliography’, Interfaces, Vol. 24, No. 2, pp.116–130.
    • (1994) Interfaces , vol.24 , Issue.2 , pp. 116-130
    • Sharda, R.1
  • 6
    • 84948516717 scopus 로고
    • Artificial neural networks: an economic perspective
    • Kuan, C.M. and White, H. (1994) ‘Artificial neural networks: an economic perspective’, Economic Reviews, Vol. 13, No. 1, pp.1–91.
    • (1994) Economic Reviews , vol.13 , Issue.1 , pp. 1-91
    • Kuan, C.M.1    White, H.2
  • 7
    • 9644258331 scopus 로고
    • Testability of the arbitrage pricing theory by neural networks
    • Trippi and E. Turban (Eds.)
    • Ahmadi, H. (1993) ‘Testability of the arbitrage pricing theory by neural networks’, in Trippi and E. Turban (Eds.) Neural Networks in Finance and Investing.
    • (1993) Neural Networks in Finance and Investing
    • Ahmadi, H.1
  • 8
    • 0001181242 scopus 로고    scopus 로고
    • Improving the pricing of options: a neural network approach
    • John Wiley & Sons, Ltd
    • Andres, U., Korn, O. and Schmitt, C. (1998) ‘Improving the pricing of options: a neural network approach’, Journal of Forecasting, John Wiley & Sons, Ltd, Vol. 17, pp.369–388.
    • (1998) Journal of Forecasting , vol.17 , pp. 369-388
    • Andres, U.1    Korn, O.2    Schmitt, C.3
  • 9
    • 0038799301 scopus 로고    scopus 로고
    • Non-linearity and exchange rates
    • John Wiley & Sons, Ltd.
    • Fernandes, M. (1998) ‘Non-linearity and exchange rates’, Journal of Forecasting, John Wiley & Sons, Ltd., Vol. 17, pp.497–514.
    • (1998) Journal of Forecasting , vol.17 , pp. 497-514
    • Fernandes, M.1
  • 10
    • 0040140607 scopus 로고
    • Stock price pattern recognition: a recurrent neural network approach
    • R. Trippi and E. Truban (Eds.)
    • Kamijo, K. and Tanigawa, T. (1993) ‘Stock price pattern recognition: a recurrent neural network approach’, in R. Trippi and E. Truban (Eds.) Neural Networks in Finance and Investing.
    • (1993) Neural Networks in Finance and Investing
    • Kamijo, K.1    Tanigawa, T.2
  • 11
    • 0030241497 scopus 로고    scopus 로고
    • Hybrid neural network models for bankruptcy predictions
    • Elsevier Science B. V
    • Lee, K.C., Han, I. and Kwon, Y. (1996) ‘Hybrid neural network models for bankruptcy predictions, Decision Support Systems, Elsevier Science B. V, Vol. 18, pp.63–72.
    • (1996) Decision Support Systems , vol.18 , pp. 63-72
    • Lee, K.C.1    Han, I.2    Kwon, Y.3
  • 12
    • 0010021683 scopus 로고
    • Constructive learning and its application to currency exchange rate forecasting
    • R. Trippi and E. Truban (Eds.)
    • Refenes, A. (1993) ‘Constructive learning and its application to currency exchange rate forecasting’, in R. Trippi and E. Truban (Eds.) Neural Networks in Finance and Investing.
    • (1993) Neural Networks in Finance and Investing
    • Refenes, A.1
  • 14
    • 0031329532 scopus 로고    scopus 로고
    • A model selection approach to real time macroeconomic forecasting under linear models and artificial neural networks
    • Swanson, N. and White, H. (1997) ‘A model selection approach to real time macroeconomic forecasting under linear models and artificial neural networks’, The Review of Economics and Statistics
    • (1997) The Review of Economics and Statistics
    • Swanson, N.1    White, H.2
  • 16
    • 0028444978 scopus 로고
    • Bankruptcy prediction using neural networks
    • Wilson, L.R. and Sharda, R. (1994) ‘Bankruptcy prediction using neural networks’, Decision Support Systems 11, pp.545–557.
    • (1994) Decision Support Systems 11 , pp. 545-557
    • Wilson, L.R.1    Sharda, R.2
  • 17
    • 0028446878 scopus 로고
    • Decision support in non-conservative domains: generalisation with neural networks
    • Dutta, S., Shekhar, S. and Wong, W.Y. (1994) ‘Decision support in non-conservative domains: generalisation with neural networks’, Decision Support Systems, Vol. 11, pp.527–544.
    • (1994) Decision Support Systems , vol.11 , pp. 527-544
    • Dutta, S.1    Shekhar, S.2    Wong, W.Y.3
  • 18
    • 0028445622 scopus 로고
    • Neural networks for decision support: problems and opportunities
    • Schocken, S. and Ariav, G. (1994) ‘Neural networks for decision support: problems and opportunities’, Decision Support Systems, II, pp.393–414
    • (1994) Decision Support Systems, II , pp. 393-414
    • Schocken, S.1    Ariav, G.2
  • 19
    • 0028449092 scopus 로고
    • Neural networks for decision support
    • Tam, Y.K. (1994) Neural networks for decision support, Decision Support Systems 11, pp.389–392.
    • (1994) Decision Support Systems 11 , pp. 389-392
    • Tam, Y.K.1
  • 20
    • 0028445055 scopus 로고
    • Integrating artificial neural networks with rule-based expert systems
    • Yoon, Y., Guimaraes, T. and Swales, G. (1994) ‘Integrating artificial neural networks with rule-based expert systems’, Decision Support Systems, pp.497–507.
    • (1994) Decision Support Systems , pp. 497-507
    • Yoon, Y.1    Guimaraes, T.2    Swales, G.3
  • 22
    • 0001683814 scopus 로고
    • Layered neural networks with Gaussian hidden units as universal approximations
    • Hartman, E.J., Keeler, J.D. and Kowalski, J.M. (1990) ‘Layered neural networks with Gaussian hidden units as universal approximations’, Neural Computation, Vol. 2, No. 2, pp.210–215.
    • (1990) Neural Computation , vol.2 , Issue.2 , pp. 210-215
    • Hartman, E.J.1    Keeler, J.D.2    Kowalski, J.M.3
  • 23
    • 0000106040 scopus 로고
    • Universal approximation using radial basis function networks
    • Park, J. and Sandberg, I.W. (1991) ‘Universal approximation using radial basis function networks’, Neural Computation, Vol. 3, No. pp.246–257.
    • (1991) Neural Computation , vol.3 , pp. 246-257
    • Park, J.1    Sandberg, I.W.2
  • 24
    • 0024991997 scopus 로고
    • Networks and the best approximation property
    • Girosi, F. and Poggio, T. (1990) ‘Networks and the best approximation property’, Biological Cybernetics 63, pp.169–176.
    • (1990) Biological Cybernetics 63 , pp. 169-176
    • Girosi, F.1    Poggio, T.2
  • 25
    • 0000043665 scopus 로고
    • On solving incorrectly posed problems and method of regularization
    • Tikhonov, A.N. (1963) ‘On solving incorrectly posed problems and method of regularization’, Doklady Akademii USSR, Vol. 151, pp.501–504.
    • (1963) Doklady Akademii USSR , vol.151 , pp. 501-504
    • Tikhonov, A.N.1
  • 26
    • 0000043666 scopus 로고
    • On regularization of ill-posed problems
    • Tikhonov, A. N., (1973) ‘On regularization of ill-posed problems’, Doklady Akademii USSR, Vol. 153, pp.49–52.
    • (1973) Doklady Akademii USSR , vol.153 , pp. 49-52
    • Tikhonov, A.N.1
  • 29
    • 84952952713 scopus 로고    scopus 로고
    • When trained by quadratic or linear programming such networks are called the support vector machines
    • When trained by quadratic or linear programming such networks are called the support vector machines.
  • 30
    • 0032392191 scopus 로고    scopus 로고
    • The efficacy of neural networks in predicting returns on stock and bond indicies
    • Desai, V., S. and Bharati, R. (1998) ‘The efficacy of neural networks in predicting returns on stock and bond indicies’, Decision Sciences, Vol. 29, No. 2, pp.405–425.
    • (1998) Decision Sciences , vol.29 , Issue.2 , pp. 405-425
    • Desai, V.S.1    Bharati, R.2
  • 32
    • 0004393134 scopus 로고
    • Connectionist approach to time series prediction: an empirical test
    • Sharda, R. and Patil, R. (1992) ‘Connectionist approach to time series prediction: an empirical test’, Journal of Intelligent Manufacturing, Vol. 3, pp.317–323.
    • (1992) Journal of Intelligent Manufacturing , vol.3 , pp. 317-323
    • Sharda, R.1    Patil, R.2
  • 33
    • 0026258339 scopus 로고
    • Time series forecasting using neural networks vs. Box-Jenkins methodology
    • Tang, Z., de Almeida, C. and Fishwick, P.A. (1991) ‘Time series forecasting using neural networks vs. Box-Jenkins methodology’, Simulation, vol. 57, No. 5, pp.303–310.
    • (1991) Simulation , vol.57 , Issue.5 , pp. 303-310
    • Tang, Z.1    de Almeida, C.2    Fishwick, P.A.3
  • 34
    • 0000393458 scopus 로고
    • Feedforward neural nets as models for time series forecasting
    • Tang, Z. and Fishwick, P.A. (1993) ‘Feedforward neural nets as models for time series forecasting’, ORSA Journal on Computing, Vol. 5, No. 4, pp.374–385.
    • (1993) ORSA Journal on Computing , vol.5 , Issue.4 , pp. 374-385
    • Tang, Z.1    Fishwick, P.A.2
  • 38
    • 0032486709 scopus 로고    scopus 로고
    • Decision support with neural networks in the management of research and development: Concepts and application to cost estimation
    • Bode, J. (1998) ‘Decision support with neural networks in the management of research and development: Concepts and application to cost estimation’, Information & Management, Vol. 34, pp.33–40.
    • (1998) Information & Management , vol.34 , pp. 33-40
    • Bode, J.1
  • 39
    • 0031336193 scopus 로고    scopus 로고
    • Cost estimation predictive modelling: regression versus neural network
    • Smith, A. and Mason, A. (1997) ‘Cost estimation predictive modelling: regression versus neural network’, The Engineering Economist, Vol. 42, p.137.
    • (1997) The Engineering Economist , vol.42 , pp. 137
    • Smith, A.1    Mason, A.2
  • 40
    • 17344372177 scopus 로고    scopus 로고
    • Comparison of artificial neural networks (ANN) with classical modelling techniques using different designs and data from a galenical study on a soil dosage form
    • Bourquin, J., Schmidli, H., Van Hoogevest, P. and Leuenberger, H. (1998) ‘Comparison of artificial neural networks (ANN) with classical modelling techniques using different designs and data from a galenical study on a soil dosage form’, European Journal of Pharmaceutical Sciences, Vol. 6, pp.287–300.
    • (1998) European Journal of Pharmaceutical Sciences , vol.6 , pp. 287-300
    • Bourquin, J.1    Schmidli, H.2    Van Hoogevest, P.3    Leuenberger, H.4
  • 42
    • 0033442924 scopus 로고    scopus 로고
    • A cross-validation analysis of neural network out-of-sample performance in exchange rate forecasting
    • Winter
    • Hu, M.Y., Zhang, G.P., Jiang, C.X. and Patuwo, B.E. (1999) ‘A cross-validation analysis of neural network out-of-sample performance in exchange rate forecasting’, Decision Sciences, Vol. 30, No. 1, Winter.
    • (1999) Decision Sciences , vol.30 , Issue.1
    • Hu, M.Y.1    Zhang, G.P.2    Jiang, C.X.3    Patuwo, B.E.4
  • 44
    • 0012035793 scopus 로고    scopus 로고
    • On testing the random-walk hypothesis: a model- comparison approach
    • Eastern Finance Association
    • Darrat, A.F. and Zhong, M. (2000) ‘On testing the random-walk hypothesis: a model- comparison approach’, The Financial Review 35, Eastern Finance Association, pp.105–124.
    • (2000) The Financial Review 35 , pp. 105-124
    • Darrat, A.F.1    Zhong, M.2
  • 46
    • 0032043525 scopus 로고    scopus 로고
    • The effect of sample size and variability of data on the comparative performance of artificial neural networks and regression
    • Markham, I. and Rakes, T.R. (1998) ‘The effect of sample size and variability of data on the comparative performance of artificial neural networks and regression’, Conputers&Operations Research, Vol. 25, pp.251–263.
    • (1998) Conputers&Operations Research , vol.25 , pp. 251-263
    • Markham, I.1    Rakes, T.R.2
  • 47
    • 80052776562 scopus 로고    scopus 로고
    • Using bidding statistics to predict completed construction cost
    • Wright, M.G. and Williams, T.P. (2001) ‘Using bidding statistics to predict completed construction cost’, The Engineering Economist, Vol. 46, No. 2, pp.114–128.
    • (2001) The Engineering Economist , vol.46 , Issue.2 , pp. 114-128
    • Wright, M.G.1    Williams, T.P.2
  • 48
    • 0035391776 scopus 로고    scopus 로고
    • A comparison of linear and non-linear statistical techniques in performance attribution
    • Chan, N.H. and Genovese, C.R. (2001) ‘A comparison of linear and non-linear statistical techniques in performance attribution’, IEEE Transactions of Neural Networks, Vol. 12, No. 4, p.922.
    • (2001) IEEE Transactions of Neural Networks , vol.12 , Issue.4 , pp. 922
    • Chan, N.H.1    Genovese, C.R.2
  • 49
    • 0026851662 scopus 로고
    • Neural network forecasting of short, noisy time series
    • Foster, W.R., Collopy, F. and Ungar, L.H. (1992) ‘Neural network forecasting of short, noisy time series’, Computers and Chemical Engineering, Vol. 16, No. 4, pp.293–297.
    • (1992) Computers and Chemical Engineering , vol.16 , Issue.4 , pp. 293-297
    • Foster, W.R.1    Collopy, F.2    Ungar, L.H.3
  • 51
    • 0030111205 scopus 로고    scopus 로고
    • A comparison of artificial neural network and time series models for forecasting commodity prices
    • Kohzadi, N., Boyd, M.S., Kermanshahi, B. and Kaastra, I. (1996) ‘A comparison of artificial neural network and time series models for forecasting commodity prices’, Neurocomputing, Vol. 10, pp.169–181.
    • (1996) Neurocomputing , vol.10 , pp. 169-181
    • Kohzadi, N.1    Boyd, M.S.2    Kermanshahi, B.3    Kaastra, I.4
  • 52
    • 0000860595 scopus 로고    scopus 로고
    • Neural networks for time series forecasts
    • Hill, T., O’Connor, M. and Remus, W. (1996) ‘Neural networks for time series forecasts’, Management Sciences, Vol. 42, No. 7, pp.1082–1092.
    • (1996) Management Sciences , vol.42 , Issue.7 , pp. 1082-1092
    • Hill, T.1    O’Connor, M.2    Remus, W.3
  • 53
    • 0003079343 scopus 로고
    • Comparative study of artificial neural network and statistical models for predicting student grade point averages
    • Gorr, W. L., Nagin D. and Szczypula, J. (1994) ‘Comparative study of artificial neural network and statistical models for predicting student grade point averages’, International Journal of Forecasting, Vol. 10, No. 1, pp.17–33.
    • (1994) International Journal of Forecasting , vol.10 , Issue.1 , pp. 17-33
    • Gorr, W.L.1    Nagin, D.2    Szczypula, J.3
  • 54
    • 0002361166 scopus 로고
    • How good are neural networks for casual forecasting?
    • Denton, J.W. (1995) ‘How good are neural networks for casual forecasting?’, The Journal of Business Forecasting, vol. 14, No. 2, pp.17–20.
    • (1995) The Journal of Business Forecasting , vol.14 , Issue.2 , pp. 17-20
    • Denton, J.W.1
  • 55
    • 0031591149 scopus 로고    scopus 로고
    • Prediction of functional characteristics of ecosystems: a comparison of artificial nerual networks and regression models
    • Paruelo, J.M. and Thomasel, F. (1997) ‘Prediction of functional characteristics of ecosystems: a comparison of artificial nerual networks and regression models’, Ecological Modelling, Vol. 98, pp.173–186.
    • (1997) Ecological Modelling , vol.98 , pp. 173-186
    • Paruelo, J.M.1    Thomasel, F.2
  • 56
    • 0035391533 scopus 로고    scopus 로고
    • A comparison of non-linear methods for predicting earnings surprise and returns
    • Dhar, V. and Chou, D. (2001) ‘A comparison of non-linear methods for predicting earnings surprise and returns’, IEEE Transactions of Neural Networks, Vol. 12, No. 4, p.907.
    • (2001) IEEE Transactions of Neural Networks , vol.12 , Issue.4 , pp. 907
    • Dhar, V.1    Chou, D.2
  • 57
    • 0040689916 scopus 로고
    • Estimating the length of the optimal TSP tour: an empirical study using regression and neural networks
    • Kwon, O., Golden, B. and Wasil, E. (1995) ‘Estimating the length of the optimal TSP tour: an empirical study using regression and neural networks’, Computers&Operations Research, Vol. 22, pp.1039–1046.
    • (1995) Computers&Operations Research , vol.22 , pp. 1039-1046
    • Kwon, O.1    Golden, B.2    Wasil, E.3
  • 58
    • 0033126073 scopus 로고    scopus 로고
    • Prediction and classification with neural network models
    • Zeng, L. (1999) ‘Prediction and classification with neural network models’, Sociological Methods & Research, p.27.
    • (1999) Sociological Methods & Research , pp. 27
    • Zeng, L.1
  • 59
    • 0029333063 scopus 로고
    • Modelling skid resistance for flexible pavements: A comparison between regression and neural network models
    • Owusu-Ababio, S. (1995) ‘Modelling skid resistance for flexible pavements: A comparison between regression and neural network models’, Transportation Research Record, No. 1501, pp.60–71.
    • (1995) Transportation Research Record , Issue.1501 , pp. 60-71
    • Owusu-Ababio, S.1
  • 60
    • 77149121380 scopus 로고    scopus 로고
    • Modelling properties of powders using artificial neural networks and regression: the case of limited data
    • Zolotariov, E. and Anwar, J. (1998) ‘Modelling properties of powders using artificial neural networks and regression: the case of limited data’, Journal of Pharmacy and Pharmacology, Vol. 50, p.190.
    • (1998) Journal of Pharmacy and Pharmacology , vol.50 , pp. 190
    • Zolotariov, E.1    Anwar, J.2
  • 61
    • 84952959339 scopus 로고
    • Neural networks versus parameter-based applications in cost estimating
    • De-la-Garza, J. and Rouhana, K.G. (1995) ‘Neural networks versus parameter-based applications in cost estimating’, Cost Engineering, p.37.
    • (1995) Cost Engineering , pp. 37
    • De-la-Garza, J.1    Rouhana, K.G.2
  • 62
    • 0026954346 scopus 로고
    • Forecasting the behaviour of multivariate time series using neural networks
    • Chakraborty, K., Hatabian, G., Mohan, C.K. and Ranka, S. (1992) ‘Forecasting the behaviour of multivariate time series using neural networks’, Neural Networks, Vol. 5, pp.961–970.
    • (1992) Neural Networks , vol.5 , pp. 961-970
    • Chakraborty, K.1    Hatabian, G.2    Mohan, C.K.3    Ranka, S.4
  • 63
    • 0029482466 scopus 로고
    • Forecasting international airline passenger traffic using neural networks
    • Nam, K. and Schaefer, T. (1995) ‘Forecasting international airline passenger traffic using neural networks’, Logistics and Transportation, Vol. 31, No. 3, pp.239–251.
    • (1995) Logistics and Transportation , vol.31 , Issue.3 , pp. 239-251
    • Nam, K.1    Schaefer, T.2
  • 64
    • 0002664811 scopus 로고
    • Applying artificial neural networks to investment analysis
    • Swales, G.S. Jr. and Yoon, Y. (1992) ‘Applying artificial neural networks to investment analysis’, Financial Analysts Journal, p.78.
    • (1992) Financial Analysts Journal , pp. 78
    • Swales, G.S.1    Yoon, Y.2
  • 67
    • 0000793695 scopus 로고
    • Neural networks offer an alternative to traditional regression
    • Robinson, R. (1991) ‘Neural networks offer an alternative to traditional regression’, Geobyte, Vol. 6.
    • (1991) Geobyte , vol.6
    • Robinson, R.1
  • 70
    • 0035392124 scopus 로고    scopus 로고
    • Modelling exchange rates: smooth transition, neural networks and linear models
    • Medeiros, M.C., Veiga, A. and Pedreira, C.E. (2001) ‘Modelling exchange rates: smooth transition, neural networks and linear models, IEEE Transactions of Neural Networks, Vol. 12, No. 4, p.755.
    • (2001) IEEE Transactions of Neural Networks , vol.12 , Issue.4 , pp. 755
    • Medeiros, M.C.1    Veiga, A.2    Pedreira, C.E.3
  • 71
    • 84952965837 scopus 로고    scopus 로고
    • Methodical madness: technical analysis and the irrationality of exchange rate forecasts
    • Chang, P.H.K. and Osler, C.L. (1999) ‘Methodical madness: technical analysis and the irrationality of exchange rate forecasts’, Economic Journal, Vol. 10, pp.91–107.
    • (1999) Economic Journal , vol.10 , pp. 91-107
    • Chang, P.H.K.1    Osler, C.L.2
  • 72
    • 0002406475 scopus 로고    scopus 로고
    • Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules
    • Gencay, R. (1999) ‘Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules’, J. Int. Econ., Vol. 47, pp.91–107.
    • (1999) J. Int. Econ. , vol.47 , pp. 91-107
    • Gencay, R.1
  • 73
    • 0000060713 scopus 로고
    • Non-linear, nonparametric, nonessential exchange rate prediction
    • Meese, R.A. and Rose, A.K. (1990) ‘Non-linear, nonparametric, nonessential exchange rate prediction’, Amer. Econ. Rev. Papers Proc. Vol. 80, pp.192–196
    • (1990) Amer. Econ. Rev. Papers Proc. , vol.80 , pp. 192-196
    • Meese, R.A.1    Rose, A.K.2
  • 74
    • 75949089711 scopus 로고
    • Comparing the modelling performance of regression and neural networks as data quality varies: a business value approach
    • Summer, M. E. Shape, Inc.
    • Bansal, A., Kauffman, J.R. and Weitz, R.R. (1993) ‘Comparing the modelling performance of regression and neural networks as data quality varies: a business value approach’, Journal of Management Information Systems, Summer, M. E. Shape, Inc., Vol. 10, No. 1, pp.11–31.
    • (1993) Journal of Management Information Systems , vol.10 , Issue.1 , pp. 11-31
    • Bansal, A.1    Kauffman, J.R.2    Weitz, R.R.3
  • 75
    • 0024895108 scopus 로고
    • Neural network models in simulation: A comparison with traditional modelling approaches
    • Washington, D.C
    • Fishwick, P.A. (1989) ‘Neural network models in simulation: A comparison with traditional modelling approaches’, in Proceedings of Winter Simulation Conference, Washington, D.C., pp.702–710.
    • (1989) Proceedings of Winter Simulation Conference , pp. 702-710
    • Fishwick, P.A.1
  • 77
    • 2942746029 scopus 로고    scopus 로고
    • Learning and Soft Computing with Support Vector Machines
    • MIT
    • Kecman, V. (2001) Learning and Soft Computing with Support Vector Machines, Neural Networks and Fuzzy Logic Models, MIT.
    • (2001) Neural Networks and Fuzzy Logic Models
    • Kecman, V.1
  • 79
    • 0031288365 scopus 로고    scopus 로고
    • Performance evaluation of neural network decision models
    • Autumn,, M. E. Shape, Inc.
    • Bharat, A.J. and Barin, N.N. (1997) ‘Performance evaluation of neural network decision models’, Journal of Management Information Systems, Autumn,, M. E. Shape, Inc., Vol. 14, No. 2, pp.201–216, pp.0742–1222
    • (1997) Journal of Management Information Systems , vol.14 , Issue.2
    • Bharat, A.J.1    Barin, N.N.2
  • 80
    • 0032172083 scopus 로고    scopus 로고
    • Inductive, evolutionary and neural computing techniques for discrimination: a comparative study
    • Bhattacharyya, S. and Pendharkar. P.C. (1998) ‘Inductive, evolutionary and neural computing techniques for discrimination: a comparative study’, Decision Sciences, Vol. 29, No. 4, pp.871–899.
    • (1998) Decision Sciences , vol.29 , Issue.4 , pp. 871-899
    • Bhattacharyya, S.1    Pendharkar., P.C.2
  • 83
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • Cybenko, G. (1989) ‘Approximation by superpositions of a sigmoidal function’, Mathematics of Control, Signals and Systems, Vol. 2, pp.304–314.
    • (1989) Mathematics of Control, Signals and Systems , vol.2 , pp. 304-314
    • Cybenko, G.1
  • 84
    • 0032123339 scopus 로고    scopus 로고
    • Runoff forecasting using RBF networks with OLS algorithm
    • ASCE
    • Fernando, D.A.K. and A.W. Jayawardena (1998) ‘Runoff forecasting using RBF networks with OLS algorithm’, Journal of Hydrologic Engineering, ASCE, Vol. 3, No. 3, pp.203–209.
    • (1998) Journal of Hydrologic Engineering , vol.3 , Issue.3 , pp. 203-209
    • Fernando, D.A.K.1    Jayawardena, A.W.2
  • 86
    • 0026221458 scopus 로고
    • Design of artificial neural networks for short-term load forecasting, Part II: Multilayer feedforward networks for peak load and velley load forecasting
    • Hsu, Y.Y. and Yang, C.C. (1991) ‘Design of artificial neural networks for short-term load forecasting, Part II: Multilayer feedforward networks for peak load and velley load forecasting’, IEE Proceedings-C: Generation, Transmission and Distribution, Vol. 138, No. 5, pp.414–418.
    • (1991) IEE Proceedings-C: Generation, Transmission and Distribution , vol.138 , Issue.5 , pp. 414-418
    • Hsu, Y.Y.1    Yang, C.C.2
  • 88
    • 0033756363 scopus 로고    scopus 로고
    • Up around the bend: linear and non-linear models of the UK economy compared
    • Johnes, G. (2000) ‘Up around the bend: linear and non-linear models of the UK economy compared’, International Review of Applied Economics, Vol. 14, No. 4.
    • (2000) International Review of Applied Economics , vol.14 , Issue.4
    • Johnes, G.1
  • 90
    • 84952966053 scopus 로고    scopus 로고
    • Are neural networks a better forecaster
    • Futures, October
    • Kudyba, S. (1998) ‘Are neural networks a better forecaster’, Technology & Trading, Futures, October
    • (1998) Technology & Trading
    • Kudyba, S.1
  • 91
    • 0033684983 scopus 로고    scopus 로고
    • Comparison of rates of linear and neural network approximation
    • Kurkova, V. and M. Sanguineti, (2000) ‘Comparison of rates of linear and neural network approximation’, 2000 IEEE, pp.277–282.
    • (2000) 2000 IEEE , pp. 277-282
    • Kurkova, V.1    Sanguineti, M.2
  • 92
    • 0030110988 scopus 로고    scopus 로고
    • Neural network prediction analysis: the bunkruptcy case
    • Leshno, M. and Spector, Y. (1996) ‘Neural network prediction analysis: the bunkruptcy case’, Neurocomputing, Vol. 10, pp.125–147.
    • (1996) Neurocomputing , vol.10 , pp. 125-147
    • Leshno, M.1    Spector, Y.2
  • 93
    • 84952958405 scopus 로고    scopus 로고
    • Sovereign debt service capacity estimation by logistic regression and neural networks
    • Autumn
    • Liu, W., Hwang, M.I. and Chen, D. (2000) ‘Sovereign debt service capacity estimation by logistic regression and neural networks’, Multinational Business Review, Autumn.
    • (2000) Multinational Business Review
    • Liu, W.1    Hwang, M.I.2    Chen, D.3
  • 94
    • 0035871395 scopus 로고    scopus 로고
    • Comparison of artificial neural networks with other statistical approaches
    • 15 April
    • Sargent, D.J. (2001) ‘Comparison of artificial neural networks with other statistical approaches’, CANCER Supplement, 15 April, Vol. 91, No. 8, pp.1636–1642.
    • (2001) CANCER Supplement , vol.91 , Issue.8 , pp. 1636-1642
    • Sargent, D.J.1
  • 95
    • 0035871573 scopus 로고    scopus 로고
    • Neural network and regression predictions of 5-year survival after colon carcinoma treatment
    • 15 April
    • Snow, P.B., Kerr, D.J., Brandt, J.M. and Rodvold, D.M. (2001) ‘Neural network and regression predictions of 5-year survival after colon carcinoma treatment’, CANCER Supplement, 15 April, Vol. 91, No. 8, pp.1637–1678.
    • (2001) CANCER Supplement , vol.91 , Issue.8 , pp. 1637-1678
    • Snow, P.B.1    Kerr, D.J.2    Brandt, J.M.3    Rodvold, D.M.4
  • 96
    • 0030717185 scopus 로고    scopus 로고
    • Practical comparison of neural networks and conventional identification methodologies
    • No. 440, IEE, 7–9 July
    • Soufian, M., Soufian, M. and Thomson, M. (1997) ‘Practical comparison of neural networks and conventional identification methodologies’, Artificial Neural Networks, No. 440, IEE, 7–9 July.
    • (1997) Artificial Neural Networks
    • Soufian, M.1    Soufian, M.2    Thomson, M.3
  • 97
    • 0033429643 scopus 로고    scopus 로고
    • Artificial neural networks versus multiple regression in tourism demand analysis
    • Uysal, M. and El Roubi, M.S. (1999) ‘Artificial neural networks versus multiple regression in tourism demand analysis’, Journal of Travel Research, Vol. 38, pp.111–118.
    • (1999) Journal of Travel Research , vol.38 , pp. 111-118
    • Uysal, M.1    El Roubi, M.S.2
  • 98
    • 84952962050 scopus 로고    scopus 로고
    • Neural networks vs. PARMA modelling: case studies of river flow prediction
    • Valenca, M. and Ludermir, T. (2000) ‘Neural networks vs. PARMA modelling: case studies of river flow prediction’, 2000 IEEE.
    • (2000) 2000 IEEE
    • Valenca, M.1    Ludermir, T.2
  • 99
    • 0035324930 scopus 로고    scopus 로고
    • Comparison of a neural net-based QSAR algorithm (PCANN) with hologram- and multiple linear regression-based QSAR approaches: application to 1,4-Dihydropyridine-based calcium channel antagonists
    • Viswanadhan, V.N., Mueller, G.A.Basak, S.C. and Weinsten, J.N. (2001) ‘Comparison of a neural net-based QSAR algorithm (PCANN) with hologram- and multiple linear regression-based QSAR approaches: application to 1,4-Dihydropyridine-based calcium channel antagonists’, J. Chem. Inf. Comput. Sci., Vol. 41, pp.505–51.
    • (2001) J. Chem. Inf. Comput. Sci. , vol.41 , pp. 505-551
    • Viswanadhan, V.N.1    Mueller, G.A.2    Basak, S.C.3    Weinsten, J.N.4
  • 100
    • 84952964906 scopus 로고    scopus 로고
    • A neural network approach to process identification and decision making
    • Auckland, New Zealand, February
    • Vojinovic, Z. (2001) ‘A neural network approach to process identification and decision making’, Proceedings of APRU International Doctoral Students Conference, Auckland, New Zealand, February.
    • (2001) Proceedings of APRU International Doctoral Students Conference
    • Vojinovic, Z.1
  • 101
    • 84952974609 scopus 로고    scopus 로고
    • Predicting stock price performance: a NN approach
    • R.R. Trippi and E. Turban Irwin Professional Publishing
    • Yoon, Y. and Swales, G. (1996) ‘Predicting stock price performance: a NN approach’, in R.R. Trippi and E. Turban Neural Networks in finance and investing, Irwin Professional Publishing, p.483.
    • (1996) Neural Networks in finance and investing , pp. 483
    • Yoon, Y.1    Swales, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.