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Machine Learning Technologies on Energy Economics and Finance: Energy and Sustainable Analytics, Volume 2 (International Series in Operations Research & Management Science #368)

By Mohammad Zoynul Abedin, Wang Yong

Business and economics, Computers and internet, General non-fiction, Science and technology

Synthetic audio, Automated braille

Summary

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 second volume of a two-volume set.

Title Details

ISBN 9783031950995
Publisher Springer Nature Switzerland
Copyright Date 2025
Book number 6759446
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Machine Learning Technologies on Energy Economics and Finance: Energy and Sustainable Analytics, Volume 2 (International Series in Operations Research & Management Science #368)

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