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Probabilistic methods can be applied to forecast volcanic activity across different timescales.
In this context, many methods can be applied to forecast renewables energy production.
Theoretically, prediction of global irradiance can be applied to forecast the energy production of PV power plant.
Although the support vector machine (SVM) can be applied to forecast solar radiation, it includes a large number of redundant variables.
Thus, some of modified logistic-like models will be applied to forecast the biogas production of China in the short term.
Various decline curve analysis (DCA) methods can be applied to forecast the production performance of hydrocarbon wells, including horizontal wells stimulated with hydraulic fracturing.
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Finally, the model is applied to forecast the behavior of a two-factor affine model.
The obtained granular model is applied to forecast three real-world time series.
Adaptive neuro fuzzy inference system (ANFIS) model [13] has been applied to forecast Internet traffic time series in [14].
During this research, multilayer ANN has been applied to forecast the input and outputs of each DMU in 5 years.
After decomposing heterogeneous data points into several homogenous regions, support vector regression (SVR) is applied to forecast financial indices.
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