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Application of Machine Learning and Deep Learning Methods to Power System Problems (Paperback, 1st ed. 2021): Morteza... Application of Machine Learning and Deep Learning Methods to Power System Problems (Paperback, 1st ed. 2021)
Morteza Nazari-Heris, Somayeh Asadi, Behnam Mohammadi-Ivatloo, Moloud Abdar, Houtan Jebelli, …
R4,592 Discovery Miles 45 920 Ships in 10 - 15 working days

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.

Application of Machine Learning and Deep Learning Methods to Power System Problems (Hardcover, 1st ed. 2021): Morteza... Application of Machine Learning and Deep Learning Methods to Power System Problems (Hardcover, 1st ed. 2021)
Morteza Nazari-Heris, Somayeh Asadi, Behnam Mohammadi-Ivatloo, Moloud Abdar, Houtan Jebelli, …
R3,731 Discovery Miles 37 310 Ships in 12 - 17 working days

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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