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Forecasting the short-term demand for electricity: Do neural networks stand a better chance?

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  • Darbellay, Georges A.
  • Slama, Marek

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  • Darbellay, Georges A. & Slama, Marek, 2000. "Forecasting the short-term demand for electricity: Do neural networks stand a better chance?," International Journal of Forecasting, Elsevier, vol. 16(1), pages 71-83.
    • Handle: RePEc:eee:intfor:v:16:y:2000:i:1:p:71-83
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    References listed on IDEAS

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    1. Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
    2. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    3. McClelland, John W. & Wetzstein, Michael E. & Musser, Wesley N., 1986. "Returns To Scale And Size In Agricultural Economics," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-5, December.
    4. Darbellay, Georges A., 1999. "An estimator of the mutual information based on a criterion for conditional independence," Computational Statistics & Data Analysis, Elsevier, vol. 32(1), pages 1-17, November.
    5. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    6. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    7. Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
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