Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …

Accurate and reliable short-term runoff prediction is of great significance to the management
of water resources optimization and reservoir flood operation. In order to improve the …

The significance of accurate short-term load forecasting (STLF) for modern power systems'
efficient and secure operation is paramount. This task is intricate due to cyclicity, non …

Projections of commodity prices have long been a significant source of dependence for
investors and the government. This study investigates the challenging topic of forecasting …

From 1 January 2010 to 15 April 2021, this study examines the challenging task of daily
regional steel price index forecasting in the east Chinese market. We train our models using …

Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …

The reform of the EU ETS markets in 2017 has induced new carbon price forecasting
challenges. This study proposes a novel decomposition-ensemble paradigm VMD …

Purpose Predicting commodity futures trading volumes represents an important matter to
policymakers and a wide spectrum of market participants. The purpose of this study is to …

Carbon trading is one of the important mechanisms used to reduce carbon dioxide
emissions. The increasing interest in the carbon trading market has heightened the need to …

With the continuous development of financial markets worldwide to tackle rapid changes
such as climate change and global warming, there has been increasing recognition of the …