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Journal Article

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

Darbellay Georges A., Sláma Marek

: International Journal of Forecasting vol.16, 1 (2000), p. 71-83

: AV0Z1075907

: GA102/95/1311, GA ČR

(eng): We address a problem faced by every supplier of electricity, i.e. forecasting the short-term electricity consumption. The introduction of new techniques has often been justifed by invoking the nonlinearity of the problem. First, we introduce a nonlinear measure of statistical dependence. Second, we analyse the linear and the nonlinear autocorrelation functions of the Czech electric comsumption. Third, we compare the predictions of nonlinear models with linear models.

: 12B

: BB

07.01.2019 - 08:39