Modeling for Energy Demand Forecasting
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چکیده
• Traditional approaches, including Box–Jenkins autoregressive integrated moving average (ARIMA) model, autoregressive and moving average with exogenous variables (ARMAX) model, seasonal autoregressive integrated moving average (SARIMA) model, exponential smoothing models [including Holt–Winters model (HW) and seasonal Holt and Winters’ linear exponential smoothing (SHW)], state space/Kalman filtering model, and linear regression model • Artificial intelligent approaches, including knowledge-based expert system (KBES) model, artificial neural networks (ANNs) model, and fuzzy inference system model • Support vector regression (SVR) model and its related hybrid/combined models
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