In today’s liberalized electricity markets, modeling and forecasting demand data are highly important for the effective management of power system. However, is a challenging task due to specific features it exhibits. These include presence extreme values, spikes or jumps, multiple periodicities, long trend, bank holiday effect. addition, forecasts required complete day as decided before physica...

Missing data are typical yet must be addressed for proper inferences or expanding datasets to guide our limnological understanding and management of aquatic systems. Interpolation methods (i.e., estimating missing values using known within the dataset) can alleviate gaps common problems. We compared seven popular interpolation predicting substantial missingness in a long-term water quality data...