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 …

Forecasting models that are trained across sets of many time series, known as Global
Forecasting Models (GFM), have shown recently promising results in forecasting …

To leverage computer vision technology to improve the accuracy of tourism demand
forecasting, a model based on deep learning with time series imaging is proposed. The …

By enhancing data accessibility, the implementation of data-driven models has been made
possible to empower strategies in relation to O&M activities. Such models have been …

Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …

Inspired by the successful use of deep learning in computer vision, in this paper we
introduce ForCNN, a novel deep learning method for univariate time series forecasting that …

The application of machine learning techniques in the field of tourism is experiencing a
remarkable growth, as they allow to propose efficient solutions to problems present in this …

Time series forecasting is fundamental for various use cases in different domains such as
energy systems and economics. Creating a forecasting model for a specific use case …

In the modern manufacturing industry, mechanical equipment plays a crucial role.
Equipment working in harsh environments for a long time is more likely to break down …