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Machine Learning Technologies on Energy Economics and Finance: Energy and Sustainable Analytics, Volume 1: 367 (International Series in Operations Research & Management Science, 367) - Hardcover
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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.
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Über die Autorin bzw. den Autor
Dr. Mohammad Zoynul Abedin is a Senior Lecturer in FinTech, at the School of Management, Swansea University, UK. He received his B.B.A. and M.B.A. degrees in finance from the University of Chittagong, Bangladesh, and his D.Phil. degree in investment theory from the Dalian University of Technology, China. His work appears on the Annals of Operations Research, International Journal of Production Research, IEEE Transactions on Industrial Informatics, to mention a few. His current research interests include business data analytics, fintech, and computational finance. He is a fellow of the Financial Management Association (FMA), and British Accounting and Finance Association (BAFA).
Dr. Wang Yong is a Professor and the Vice Dean at the School of Statistics, Dongbei University of Finance and Economics (DUFE), China. Dr. Yong was awarded the Outstanding Professor by DUFE, and is also the chief expert of major projects at the National Social Science Foundation of China. His main research interests are energy economics, environmental-economic system analysis, and policy optimization. He has published more than 70 papers in reputable academic journals, including Annals of Operations Research, Technological Forecasting & Social Change, Journal of Environmental Management, Renewable and Sustainable Energy Reviews, and other prestigious journals.
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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.
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Machine Learning Technologies on Energy Economics and Finance (eng)
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Machine Learning Technologies on Energy Economics and Finance
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Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031948610
ISBN 13: 9783031948619
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 332 pp. Englisch. Bestandsnummer des Verkäufers 9783031948619
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Machine Learning Technologies on Energy Economics and Finance
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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 344 pp. Englisch. Bestandsnummer des Verkäufers 9783031948619
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Machine Learning Technologies on Energy Economics and Finance : Energy and Sustainable Analytics, Volume 1
Verlag:
Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031948610
ISBN 13: 9783031948619
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Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783031948619
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Machine Learning Technologies on Energy Economics and Finance: Energy and Sustainable Analytics, Volume 1 (International Series in Operations Research & Management Science, 367)
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Machine Learning Technologies on Energy Economics and Finance (Hardcover)
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ISBN 10: 3031948610
ISBN 13: 9783031948619
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Hardcover. Zustand: new. Hardcover. 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 sectorssuch 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9783031948619
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Machine Learning Technologies on Energy Economics and Finance: Energy and Sustainable Analytics: Vol 1
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Hardcover. Zustand: Brand New. 300 pages. 9.25x6.10x9.21 inches. In Stock. Bestandsnummer des Verkäufers x-3031948610
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Machine Learning Technologies on Energy Economics and Finance (Hardcover)
Verlag:
Springer International Publishing AG, Cham, 2025
ISBN 10: 3031948610
ISBN 13: 9783031948619
Neu
Hardcover
Anbieter: Grand Eagle Retail, Mason, OH, USA
Verkäuferbewertung 5 von 5 Sternen
Hardcover. Zustand: new. Hardcover. 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 sectorssuch 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9783031948619
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