Forecasting electric load demand through advanced statistical techniques
Artículo de revista
2020
Journal of Physics: Conference Series
Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate characteristics of the past models of the same series, according to their autocorrelation. This work compares advanced statistical methods for determining the demand for electricity in Colombia, including the SARIMA, econometric and Bayesian methods.
- Artículos científicos [3154]
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Forecasting electric load demand through advanced statistical techniques.pdf
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Descripción: Forecasting Electric Load Demand through Advanced Statistical.pdf
Título: Forecasting Electric Load Demand through Advanced Statistical.pdf
Tamaño: 1.481Mb
PDFLEER EN FLIP
Título: Forecasting electric load demand through advanced statistical techniques.pdf
Tamaño: 680.4Kb
PDFLEER EN FLIP
Descripción: Forecasting Electric Load Demand through Advanced Statistical.pdf
Título: Forecasting Electric Load Demand through Advanced Statistical.pdf
Tamaño: 1.481Mb
PDFLEER EN FLIP
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