machine learning cyber physical systems (206 Ergebnisse)

121 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.

Kartoniert / Broschiert. Zustand: New.

Zustand: Gut. Zustand: Gut | Seiten: 396 | Sprache: Englisch | Produktart: Bücher.

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Kartoniert / Broschiert. Zustand: New.

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Zustand: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren, leicht bestoßen/minor shelfwear, slightly bumped. Edited by Vipin Kumar Kukkala and Sudeep Pasricha. With contributions by Wanli Chang, Nan Chen, Shuai Zhao, Xiaotian Dai et al. XV,789 Seiten, gebunden (Springer-Verlag 2023). Statt EUR 117,69. Gewicht: 137 g - Gebunden/Gebundene Ausgabe - Sprache: Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 808 pp. Englisch.

hardcover. Zustand: Good. Damage on front cover. Pages are clean, text intact and unmarred.

Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Threats in Cyber-Physical Systems is a cutting-edge exploration of the potential applications of machine learning in the context of cyber-physical systems. By examining the complex relationships between machine learning, cybersecurity, and cyber-physical systems, this book highlights the unique challenges and opportunities presented by the application of machine learning to threat detection in these systems. From the development of predictive models to the integration of anomaly detection algorithms, this book covers a wide range of topics, providing a comprehensive understanding of the intricate relationships between machine learning, cybersecurity, and cyber-physical systems. By exploring the use of machine learning to detect threats in cyber-physical systems, readers will gain a deeper appreciation for the potential of this approach to revolutionize the way we protect these critical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. The application of machine learning in the design of next-generation cyber-physical systems has the potential to revolutionize the way we interact with and control complex systems. In 'Machine Learning in Designing Next-Gen Cyber-Physical Systems', experts in the field explore the latest advancements in AI-powered design tools, from machine learning algorithms that can optimize system performance to computer vision systems that can analyze and interpret sensor data. By examining the applications of machine learning in cyber-physical system design, from the development of autonomous vehicles to the creation of smart cities, this book provides a comprehensive overview of the exciting possibilities presented by this rapidly evolving field. With its focus on the latest research and developments, 'Machine Learning in Designing Next-Gen Cyber-Physical Systems' is an essential resource for anyone interested in the cutting-edge of AI and its applications in cyber-physical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

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Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Cyber-physical systems, which seamlessly integrate the physical and digital realms, are poised to transform numerous industries. This book provides a detailed examination of the role of machine learning in powering these systems, highlighting the vast potential for improved efficiency, accuracy, and adaptability. By exploring the intricacies of machine learning in the context of cyber-physical systems, the book offers a forward-thinking perspective on the future of technological innovation. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

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Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Cyber-physical systems are increasingly ubiquitous in modern life, from smart homes to industrial control systems. However, these systems are also vulnerable to a range of threats, from hacking to sabotage. Using Machine Learning to Detect Threats in Cyber-Physical Systems offers a cutting-edge exploration of the latest machine learning techniques for detecting and mitigating these threats. By examining the intersection of machine learning and cybersecurity, the author reveals new possibilities for the detection and prevention of cyber-physical threats. Through a series of case studies and theoretical analyses, this book provides a comprehensive guide to the latest machine learning techniques for cyber-physical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. The increasing reliance on cyber-physical systems has raised important questions about the role of machine learning in these systems. In 'Machine Learning Tactics in Cyber-Physical Systems', we investigate the challenges and opportunities presented by the integration of machine learning and cyber-physical systems. We examine the development of machine learning algorithms that can identify and respond to complex patterns in cyber-physical systems, and discuss the importance of adaptability, resilience, and security in these systems. This book provides a comprehensive overview of the current state of the field, and explores the potential applications of machine learning in cyber-physical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Machine Learning for Anomaly Detection in Cyber Physical Systems is a cutting-edge guide to applying machine learning techniques to anomaly detection in cyber physical systems. This book provides a detailed exploration of the principles and methods used in machine learning, including supervised and unsupervised learning, clustering, and classification. By applying machine learning to real-world problems, readers can develop effective solutions to anomaly detection and diagnosis in cyber physical systems. With its focus on practical applications and case studies, Machine Learning for Anomaly Detection in Cyber Physical Systems offers a hands-on approach to mastering the art of machine learning. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Machine Learning in Designing Adaptive Cyber-Physical Systems presents a groundbreaking exploration of the application of machine learning techniques in designing adaptive cyber-physical systems. This book showcases the latest advancements in machine learning and control theory, from reinforcement learning to model predictive control, and demonstrates their potential for developing adaptive systems that can learn from experience and adapt to changing environments. By applying these cutting-edge methods, researchers and students will gain a deeper understanding of the complex relationships between different system components and the insights they offer into the behavior of adaptive systems. With its focus on adaptive cyber-physical systems and machine learning, this book provides a valuable resource for scholars seeking to improve the efficiency and effectiveness of complex systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. 'Cyber-Physical Systems Powered by Machine Learning' explores the integration of AI into interconnected physical and computational systems. It details how machine learning enhances system resilience, predictive maintenance, and autonomous control in sectors like manufacturing, transportation, and energy. The book underscores the transformative influence of AI on the functionality, security, and efficiency of cyber-physical infrastructures. It provides insights into designing intelligent systems capable of adapting to complex, real-world environments. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Machine learning is a powerful tool that enables the development of intelligent systems that can learn from data and adapt to changing conditions. In 'Machine Learning for Cyber-Physical Systems', the authors provide a comprehensive examination of the fundamental principles and techniques that underlie this field, from the development of machine learning algorithms to the use of deep learning architectures. By exploring the underlying technology that governs machine learning in cyber-physical systems, the book offers a nuanced understanding of the complex interactions that occur between machine learning systems and cyber-physical systems. From the study of machine learning-based control systems to the analysis of machine learning-driven decision-making, this book provides a detailed exploration of the key phenomena that govern machine learning in cyber-physical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Threats in Cyber-Physical Systems examines how advanced algorithms can identify vulnerabilities and malicious activities within interconnected systems. The book covers various machine learning techniques tailored for real-time threat detection, emphasizing the importance of proactive security measures in critical infrastructure. It provides insights into developing resilient cyber-physical environments through intelligent monitoring and anomaly detection. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.