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Synopsis
Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
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À propos de l?auteur
Balamurugan Easwaran, College of Business Administration, Department of Accounting and Finance, A' Sharqiyah University, Oman
Kamal Kant Hiran, Sir Padampat Singhania University, India
Sangeetha Krishnan, University of Africa, Toru-Orua, Nigeria
Ruchi Doshi, Azteca University, Mexico
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurBusiness Science Reference
- Date d'édition2022
- ISBN 10 1799893081
- ISBN 13 9781799893080
- ReliureRelié
- Langueanglais
- Nombre de pages400
- ÉditeurEaswaran Balamurugan, Vieira Elisabete S., Madaleno Mara, Azevedo Graça
- Coordonnées du fabricantnon disponible
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Real-time Applications of Machine Learning in Cyber-physical Systems (Advances in Computational Intelligence and Robotics)
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Real-Time Applications of Machine Learning in Cyber-Physical Systems
Edité par
Engineering Science Reference, 2022
ISBN 10 : 1799893081
ISBN 13 : 9781799893080
Neuf
Couverture rigide
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses forensic accounting techniques and explores how forensic accountants add value while investigating claims of fraud. The book also highlights the corporate benefits of a forensic accounting audit and the acceptance of this evidence in a court of la. N° de réf. du vendeur 635886193
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Real-Time Applications of Machine Learning in Cyber-Physical Systems
Edité par
Engineering Science Reference, 2022
ISBN 10 : 1799893081
ISBN 13 : 9781799893080
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians. N° de réf. du vendeur 9781799893080
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