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Application of Machine Learning and Deep Learning Methods to Power System Problems (Power Systems)

By: Behnam Mohammadi-Ivatloo (Edited by) , Houtan Jebelli (Edited by) , Milad Sadat-Mohammadi (Edited by) , Moloud Abdar (Edited by) , Morteza Nazari-Heris (Edited by) , Somayeh Asadi (Edited by)

Extended Catalogue

Ksh 29,650.00

Format: Hardback or Cased Book

ISBN-10: 3030776956

ISBN-13: 9783030776954

Collection / Series: Power Systems

Collection Type: Publisher collection

Edition statement: 2021 ed.

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Oct 21st, 2021

Publication Status: Active

Product extent: 391 Pages

Product Classification / Subject(s): Electrical engineering
Machine learning

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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.
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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