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2015 16th International Scientific Conference on Electric Power Engineering (EPE)
In this article we present the idea of short-term load cross-forecasting. This approach combines forecasts generated by two models which learn on input data defined in different ways: as daily and weekly patterns. Pattern definitions described in this work simplify the forecasting problem by filtering out the trend and seasonal variations. The nonstationarity in mean and variance is also eliminated. Simplified relationships between predictors and output variables are modeled locally usingdoi:10.1109/epe.2015.7161178 fatcat:ggcylelztfgc3epg27der557ye