Machine Learning Technologies on Energy Economics and Finance

Analyzing Global Energy Patterns: Clustering Countries and Predicting Trends Towards Achieving Sustainable Development Goals.- Access to Energy Finance: Development of Renewable Energy in Bangladesh.- Explainable AI in Energy Forecasting: Understanding Natural Gas Consumption through Interpretable Machine Learning Models.- An Extensive Statistical Analysis of Time Series Modelling and Forecasting of Crude Oil Prices.- Comparative analysis of selected emerging economies energy transition scenario: A transition pathway for the continental neighbours.- Forecasting Energy Prices using Machine Learning Algorithms: A Comparative Analysis.- An Evidence-based Explainable AI Approach for Analyzing the Influence of CO2 Emissions on Sustainable Economic Growth.- BLDAR: A Blending Ensemble Learning Approach for Primary Energy Consumption Analysis.- Analyzing Biogas Production in Livestock Farms Using Explainable Machine Learning.- Application of Machine Learning Techniques in the Analysis of Sustainable Energy Finance.- Machine Learning and Deep Learning Strategies for Sustainable Renewable Energy: A Comprehensive Review.- Efficient Gasoline Spot Price Prediction using Hyperparameter Optimization and Ensemble Machine Learning Approach.- The Implications of Energy Transition and Development of Renewable Energy on Sustainable Development Goals of Two Asian Tigers.