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(Ebook) Application of Machine Learning and Deep Learning Methods to Power System Problems (Power Systems) by Morteza Nazari-Heris (editor), Somayeh Asadi (editor), Behnam Mohammadi-Ivatloo (editor), Moloud Abdar (editor), Houtan Jebelli (editor), Milad Sadat-Mohammadi (editor) ISBN 9783030776954, 3030776956

Name: (Ebook) Application of Machine Learning and Deep Learning Methods to Power System Problems (Power Systems) by Morteza Nazari-Heris (editor), Somayeh Asadi (editor), Behnam Mohammadi-Ivatloo (editor), Moloud Abdar (editor), Houtan Jebelli (editor), Milad Sadat-Mohammadi (editor) ISBN 9783030776954, 3030776956
SKU: EBN-35394270
Price: 32 USD
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Rating: 5 (6 reviews)

SKU: EBN-35394270

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Instant download (eBook) Application of Machine Learning and Deep Learning Methods to Power System Problems (Power Systems) after payment.

Authors:Morteza Nazari-Heris (editor), Somayeh Asadi (editor), Behnam Mohammadi-Ivatloo (editor), Moloud Abdar (editor), Houtan Jebelli (editor), Milad Sadat-Mohammadi (editor)

Pages:400 pages.

Year:2021

Editon:1st ed. 2021

Publisher:Springer

Language:english

File Size:11.51 MB

Format:pdf

ISBNS:9783030776954, 3030776956

Categories: Ebooks

Product desciption

(Ebook) Application of Machine Learning and Deep Learning Methods to Power System Problems (Power Systems) by Morteza Nazari-Heris (editor), Somayeh Asadi (editor), Behnam Mohammadi-Ivatloo (editor), Moloud Abdar (editor), Houtan Jebelli (editor), Milad Sadat-Mohammadi (editor) ISBN 9783030776954, 3030776956

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

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