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  • Dolgoročno napovedovanje brez neodvisnih napovednikov
    Bizjak, Boris, 1957-
    A large variety of statistical and artificial intelligence techniques have been developed for longterm load forecasting; Similar-week approach, Regression methods, Fuzzy logic, Support vector ... machines and Time series. Timeseries methods are based on the assumption that the data have an internal structure, such as autocorrelation, trend, or seasonal variation. Time series forecasting methods detect and explore such a structure. Time series have beenused for decades in such fields as economics, digital signal processing, as well as electric load forecasting. In particular, ARMA (autoregressive moving average), ARIMA (autoregressive integrated moving average), ARMAX (autoregressive moving average with exogenous variables), and ARIMAX (autoregressive integrated moving average with exogenous variables) are the most often used classical time series methods. ARMA models are usually used for stationary processes while ARIMA is an extension of ARMA to nonstationary processes. ARMA and ARIMA use the time and load as the only input parameters.
    Vir: Zbornik devetnajste mednarodne Elektrotehniške in računalniške konference ERK 2010, Portorož, Slovenija, 20.-22. september 2010 (Zv. A, str. 484-487)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2010
    Jezik - slovenski
    COBISS.SI-ID - 14489110

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