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Published by Elsevier - Health Sciences Division, 2023
ISBN 10: 0323999042 ISBN 13: 9780323999045
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Taschenbuch. Condition: Neu. Monitoring and Control of Electrical Power Systems using Machine Learning Techniques | Emilio Barocio Espejo (u. a.) | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2023 | Elsevier Inc | EAN 9780323999045 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Add to basketCondition: New. Covers advanced applications and solutions for monitoring and control of electrical power systems using machine learning techniques for transmission and distribution systems Provides deep insight into power quality disturbance detection an.
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Add to basketPaperback. Condition: Brand New. 296 pages. 9.00x6.00x0.87 inches. In Stock. This item is printed on demand.
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Published by Elsevier - Health Sciences Division Jan 2023, 2023
ISBN 10: 0323999042 ISBN 13: 9780323999045
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms. 352 pp. Englisch.
Language: English
Published by Elsevier Science & Technology, Elsevier, 2023
ISBN 10: 0323999042 ISBN 13: 9780323999045
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms.