Among various time series (TS) forecasting methods, ensemble forecast is extensively
acknowledged as a promising ensemble approach achieving great success in research and …

Collections of time series formed via aggregation are prevalent in many fields. These are
commonly referred to as hierarchical time series and may be constructed cross-sectionally …

Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

Sales forecasting is important in production and supply chain management. It affects firms'
planning, strategy, marketing, logistics, warehousing and resource management. While …

Sales volume forecasting is of great significance to E-commerce companies. Accurate sales
forecasting enables managers to make reasonable resource allocation in advance. In this …

It has been demonstrated that local prediction approaches show better prediction
performance compared with global ones. The paper proposes a novel local prediction …

The rapid rise of many e-commerce platforms for individual consumers has generated a
large amount of text-based data, and thus researchers have begun to experiment with text …

When cryptocurrency markets generate billions of dollars, it becomes interesting to forecast
variation in volume of transactions for better trading and for better management of …

A geometric interpretation is developed for so-called reconciliation methodologies used to
forecast time series that adhere to known linear constraints. In particular, a general …

In multivariate time series forecasting tasks, expanding forecast length and improving
forecast efficiency is an urgent need for practical applications. Accurate long-term …