A short-term wind power forecasting method based on multivariate signal decomposition and variable selection

T Yang, Z Yang, F Li, H Wang - Applied Energy, 2024 - Elsevier
Accurate and effective short-term wind power forecasting is vital for the large-scale
integration of wind power generation into the power grid. However, due to the intermittence …

Estimation of global natural gas spot prices using big data and symbolic regression

L Stajić, R Praksová, D Brkić, P Praks - Resources Policy, 2024 - Elsevier
This article provides an estimation of future natural gas spot prices on the global
international market based on symbolic regression where the sensitivity analysis is …

Fossil energy market price prediction by using machine learning with optimal hyper-parameters: A comparative study

S Lahmiri - Resources Policy, 2024 - Elsevier
Fossil energy markets are important commodities, and their price fluctuations impact
worldwide economy and financial markets. Hence, it is essential to forecast the prices of …

Point and interval forecasting for wine prices: an approach based on artificial intelligence

H Cui, H Guo, J Wang, Y Wang - International Journal of …, 2024 - emerald.com
Purpose With the rise in wine consumption, accurate wine price forecasts have significantly
impacted restaurant and hotel purchasing decisions and inventory management. This study …

Do multisource data matter for NGP prediction? Evidence from the G-LSTM model

J Hao, S Shang, J Yuan, J Li - Heliyon, 2024 - cell.com
Precisely predicting natural gas prices (NGPs) is important because it can provide the
necessary decision-making basis for energy scheduling, planning and control. However …

Artificial Intelligence in Natural Resources Management: Selected Case Studies from Africa

M Kapatamoyo - 2024 - econstor.eu
This paper explores Artificial Intelligence (AI)'s transformative role in digital transformation
and its implications for Africa's socio-economic development. We examine how AI's …