05070nam 22007455 450 991101875260332120250725130239.09783031948626(electronic bk.)978303194861910.1007/978-3-031-94862-6(MiAaPQ)EBC32235808(Au-PeEL)EBL32235808(CKB)39719245900041(DE-He213)978-3-031-94862-6(EXLCZ)993971924590004120250725d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning Technologies on Energy Economics and Finance Energy and Sustainable Analytics, Volume 1 /edited by Mohammad Zoynul Abedin, Wang Yong1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (413 pages)International Series in Operations Research & Management Science,2214-7934 ;367Print version: Abedin, Mohammad Zoynul Machine Learning Technologies on Energy Economics and Finance Cham : Springer,c2025 9783031948619 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.This book explores the latest innovations in energy economics and finance, with a particular focus on the role of machine learning algorithms in advancing the energy sector. It examines key factors shaping this field, including market structures, regulatory frameworks, environmental impacts, and the dynamics of the global energy market. It discusses the critical application of machine learning (ML) in energy financing, introducing predictive tools for forecasting energy prices across various sectors—such as crude oil, electricity, fuelwood, solar, and natural gas. It also addresses how ML can predict investor behavior and assess the efficiency of energy markets, with a focus on both the opportunities and challenges in renewable energy and energy finance. This book serves as a comprehensive guide for academics, practitioners, financial managers, stakeholders, government officials, and policymakers who seek strategies to enhance energy systems, reduce costs and uncertainties, and optimize revenue for economic growth. This is the first volume of a two-volume set.International Series in Operations Research & Management Science,2214-7934 ;367Production managementBusiness information servicesFinancial engineeringMachine learningEnergy policyEnergy policySustainabilityOperations ManagementIT in BusinessFinancial Technology and InnovationMachine LearningEnergy Policy, Economics and ManagementSustainabilityProduction management.Business information services.Financial engineering.Machine learning.Energy policy.Energy policy.Sustainability.Operations Management.IT in Business.Financial Technology and Innovation.Machine Learning.Energy Policy, Economics and Management.Sustainability.658.5Abedin Mohammad Zoynul1837078Yong Wang1383645MiAaPQMiAaPQMiAaPQ9911018752603321Machine Learning Technologies on Energy Economics and Finance4415428UNINA