In this paper, a new prediction interval model based on a joint supervision loss function for capturing the uncertainties associated with the modeled phenomenon is described. This model provides the upper and lower bounds ...

The existing uncertainties during the operation of processes could strongly affect the performance of forecasting systems, control strategies and fault detection systems when they are not considered in the design. Because ...

Usual point and interval forecasting based on the autoregressive integrated moving average models (ARIMA) may not be suitable for modelling variables defined over the interval (0, 1). In fact, such forecasting effect ...

Prediction interval modelling has been proposed in the literature to characterize uncertain phenomena and provide useful information from a decision-making point of view. In most of the reported studies, assumptions about ...

Millennium Institute Complex Engineering Systems ICM: P-05-004-F CONICYT: FBO16 National Fund for Science and Technology 1140775 CONICYT/FONDAP/15110019

Microgrids have emerged as an alternative to alleviate increasing energy demands. However, because microgrids are primarily based on nonconventional energy sources (NCES), there is high uncertainty involved in their ...

Electricity load forecasting is an essential tool for the effective power grid operation and for energy markets. However, the lack of accuracy on the estimation of the electricity demand may cause an excessive or insufficient ...

The traditional methods of building prediction intervals for time series assume that the model parameters are known and the errors are Gaussian. When such assumptions are not true, the prediction intervals possess a coverage ...

Energy management systems (EMSs) are used for operators to optimize, monitor, and control the performance of a power system. In microgrids, the EMS automatically coordinates the energy sources aiming to supply the demand. ...