Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

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

The M4 Competition follows on from the three previous M competitions, the purpose of which
was to learn from empirical evidence both how to improve the forecasting accuracy and how …

This paper presents the winning submission of the M4 forecasting competition. The
submission utilizes a dynamic computational graph neural network system that enables a …

Time series forecasting has been a widely explored task of great importance in many
applications. However, it is common that real-world time series data are recorded in a short …

In this study, we present the results of the M5 “Accuracy” competition, which was the first of
two parallel challenges in the latest M competition with the aim of advancing the theory and …

The M5 competition follows the previous four M competitions, whose purpose is to learn from
empirical evidence how to improve forecasting performance and advance the theory and …

The use of wind energy plays a vital role in society owing to its economic and environmental
importance. Knowing the wind power generation within a specific time window is useful for …

The decomposition of time series into components is an important task that helps to
understand time series and can enable better forecasting. Nowadays, with high sampling …

In many supply chains, firms staged in upstream of the chain suffer from variance
amplification emanating from demand information distortion in a multi-stage supply chain …