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.
| ISBN: | 9783030776985 |
| Publication date: | 22nd October 2022 |
| Author: | Morteza NazariHeris |
| Publisher: | Springer Nature Switzerland AG |
| Format: | Paperback |
| Pagination: | 391 pages |
| Series: | Power Systems |
| Genres: |
Electrical engineering Machine learning |
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.
Application of Machine Learning and Deep Learning Methods to Power System Problems features in the following genres: Electrical engineering, Machine learning
Paperback, Hardback. £116.99, down from the £129.99 cover price. Not Available.
Application of Machine Learning and Deep Learning Methods to Power System Problems was written by Morteza NazariHeris and published by Springer Nature Switzerland AG
Application of Machine Learning and Deep Learning Methods to Power System Problems has 391 pages
Yes it is part of Power Systems series
£116.99, reduced from £129.99. Not Available.