LEADER 04981nam 22007455 450 001 9911020429003321 005 20250807130442.0 010 $a3-031-95099-2 024 7 $a10.1007/978-3-031-95099-5 035 $a(MiAaPQ)EBC32256164 035 $a(Au-PeEL)EBL32256164 035 $a(CKB)40138052700041 035 $a(DE-He213)978-3-031-95099-5 035 $a(EXLCZ)9940138052700041 100 $a20250807d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning Technologies on Energy Economics and Finance $eEnergy and Sustainable Analytics, Volume 2 /$fedited by Mohammad Zoynul Abedin, Wang Yong 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (435 pages) 225 1 $aInternational Series in Operations Research & Management Science,$x2214-7934 ;$v368 311 08$a3-031-95098-4 327 $aGreen Driving: Harnessing Machine Learning to Predict Vehicle Carbon Footprints and Interpreting Results with Explainable AI -- A Comparative Evaluation of Deep Neural Networks for Electricity Price Forecasting -- Energy Forecasting Utilizing CNN-LSTM Attention Mechanism: Empirical Evidence from the Spanish Electricity Market -- Feature Selection and Explainable AI For Transparent Windmill Power Forecasting -- Improving the Analysis of CO2 Emissions with a Filter and Imputation-Based Processing Method -- A Study on the Efficacy of Machine Learning and Ensemble Learning in Wind Power Generation Analysis -- Predicting Solar Radiation: A Fusion Approach with CatBoost and Random Forest Ensemble Enhanced by Explainable AI -- Modeling Nuclear Fusion Reaction Occurrence with Advanced Deep Learning Techniques: Insights from LIME and SMOTE -- A Critical Study on LSTM AND TRANSFORMER Models for Financial Analysis and Forecasting -- Exploring Feature Selection Techniques in Predicting Indian Household Electricity Consumption -- Constructing Women Empowerment Indices-based on Kernel PCA and Evaluating Its Determinants: Evidence from BDHS -- An Ensemble Machine Learning Approach to Predicting CO2 Emission Rates: Evidence from Denmark's Energy Data Service -- Smart Grid Stability Analysis with Interpretable Machine Learning and Deep Learning Models -- Weather as a Critical Component in Investment Strategies: Insights for Stakeholders. 330 $aThis book explores the latest innovations in energy economics and finance, with a particular focus on the role of machine learning algorithms in advancing the energy sector. It examines key factors shaping this field, including market structures, regulatory frameworks, environmental impacts, and the dynamics of the global energy market. It discusses the critical application of machine learning (ML) in energy financing, introducing predictive tools for forecasting energy prices across various sectors?such as crude oil, electricity, fuelwood, solar, and natural gas. It also addresses how ML can predict investor behavior and assess the efficiency of energy markets, with a focus on both the opportunities and challenges in renewable energy and energy finance. This book serves as a comprehensive guide for academics, practitioners, financial managers, stakeholders, government officials, and policymakers who seek strategies to enhance energy systems, reduce costs and uncertainties, and optimize revenue for economic growth. This is the second volume of a two-volume set. 410 0$aInternational Series in Operations Research & Management Science,$x2214-7934 ;$v368 606 $aProduction management 606 $aBusiness information services 606 $aFinancial engineering 606 $aMachine learning 606 $aEnergy policy 606 $aEnergy policy 606 $aSustainability 606 $aOperations Management 606 $aIT in Business 606 $aFinancial Technology and Innovation 606 $aMachine Learning 606 $aEnergy Policy, Economics and Management 606 $aSustainability 615 0$aProduction management. 615 0$aBusiness information services. 615 0$aFinancial engineering. 615 0$aMachine learning. 615 0$aEnergy policy. 615 0$aEnergy policy. 615 0$aSustainability. 615 14$aOperations Management. 615 24$aIT in Business. 615 24$aFinancial Technology and Innovation. 615 24$aMachine Learning. 615 24$aEnergy Policy, Economics and Management. 615 24$aSustainability. 676 $a658.5 700 $aAbedin$b Mohammad Zoynul$01837078 701 $aYong$b Wang$01383645 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020429003321 996 $aMachine Learning Technologies on Energy Economics and Finance$94415428 997 $aUNINA