Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

Forecasting has been an essential part of the power and energy industry. Researchers and
practitioners have contributed thousands of papers on forecasting electricity demand and …

Quantifying uncertainties in the prediction of building energy consumption is critical to
building energy management systems. In this study, a deep-learning-based interval …

Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

This paper describes the M5 “Uncertainty” competition, the second of two parallel
challenges of the latest M competition, aiming to advance the theory and practice of …

Forecasts are always wrong, otherwise, they are merely deterministic calculations. Besides
leveraging advanced forecasting methods, post-processing has become a standard practice …

Accurate carbon price forecasting is essential to reduce carbon dioxide emissions and slow
down global warming. However, a key issue in the carbon trading market is the diversity and …

Solar irradiance forecasting is essential in renewable energy grids amongst others for back-
up programming, operational planning, and short-term power purchases. This study focuses …

The COVID-19 pandemic has placed forecasting models at the forefront of health policy
making. Predictions of mortality, cases and hospitalisations help governments meet …

Accurate carbon price forecasting can provide policymakers with a reasonable basis for
carbon pricing. Interval-valued carbon price forecasting could provide sufficient information …