We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long鈥恟ange dependence is taken into account. Using Monte Carlo simulations, ...
The P2G technology can reduce wind farm forecast errors and provide a secondary control reserve [15]. In [16], the potential of power-to-gas technology as an energy balancing system was evaluated on an economic, energy and environmental basis. A stochastic mixed complementarity model was ...
Weather information 514 includes forecast models rather than raw data. Timing and severity prediction 502 uses all available information to make risk prediction 516. Risk prediction 516 specifies the risks associated with the chaotic event. For example, risk prediction 516 may predict the dangers of ...
We propose a near optimal test for structural breaks of unknown timing when the purpose of the analysis is to obtain accurate forecasts under square error loss. A bias-variance trade-off exists under square forecast error loss, which implies that small structural breaks should be ignored. We ...
Short Term Demand Forecast using a Bank of Neural Network Models Trained using Genetic Algorithms for the Optimal Management of Drinking Water Networks. J. Hydroinform. 2016, 19, 1–16. [Google Scholar] [CrossRef] [Green Version] Perez, R.; Kivalov, S.; Schlemmer, J.; Hemker, K.; ...