Machine Learning Technologies on Energy Economics and Finance

Energy and Sustainable Analytics, Volume 1
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,

Éditeur :

Springer

Paru le : 2025-07-25

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...
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Éditeur

Collection
n.c

Parution
2025-07-25

Pages
332 pages

EAN papier
9783031948619

Auteur(s) du livre


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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9783031948626
Prix
179,34 €
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
42015 Ko
EAN EPUB
9783031948626
Prix
179,34 €
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
28170 Ko

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