Îïèñàíèå: This book constitutes the proceedings of the Third International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021, which was held virtually due to the COVID-19 pandemic. The 19 long revised papers and 1 short contribution were carefully selected from 32 submissions.
Îïèñàíèå: This book constitutes the refereed proceedings of the 13th PLAIS EuroSymposium 2021 which was held in Sopot, Poland, on September 23, 2021. The objective of the PLAIS EuroSymposium 2021 is to promote and develop high quality research on all issues related to digital transformation.
Àâòîð: Easwaran Balamurugan, Hiran Kamal Kant, Krishnan Sangeetha Íàçâàíèå: Real-Time Applications of Machine Learning in Cyber-Physical Systems ISBN: 179989309X ISBN-13(EAN): 9781799893097 Èçäàòåëüñòâî: Mare Nostrum (Eurospan) Ðåéòèíã: Öåíà: 23199.00 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.
Îïèñàíèå: 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.
Àâòîð: Mundada Monica R., Seema S., K. G. Srinivasa Íàçâàíèå: Deep Learning Applications for Cyber-Physical Systems ISBN: 1799881628 ISBN-13(EAN): 9781799881629 Èçäàòåëüñòâî: Mare Nostrum (Eurospan) Ðåéòèíã: Öåíà: 29522.00 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.
Îïèñàíèå: Provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analysing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems.
Àâòîð: Mundada Monica R., Seema S., K. G. Srinivasa Íàçâàíèå: Deep Learning Applications for Cyber-Physical Systems ISBN: 179988161X ISBN-13(EAN): 9781799881612 Èçäàòåëüñòâî: Mare Nostrum (Eurospan) Ðåéòèíã: Öåíà: 39085.00 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.
Îïèñàíèå: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications.
Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
Àâòîð: Davide Calvaresi; Amro Najjar; Michael Schumacher; Íàçâàíèå: Explainable, Transparent Autonomous Agents and Multi-Agent Systems ISBN: 303030390X ISBN-13(EAN): 9783030303907 Èçäàòåëüñòâî: Springer Ðåéòèíã: Öåíà: 6986.00 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.
Îïèñàíèå: This book constitutes the proceedings of the First International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2019, held in Montreal, Canada, in May 2019. The 12 revised and extended papers presented were carefully selected from 23 submissions. explainable agent simulations;
Îïèñàíèå: Proposing the concept of real-world data circulation (RWDC), this book presents various practical and industry-related studies in human, mechanical, and social data domains.
Îïèñàíèå: This book focuses on new methods, architectures, and applications for the management of Cyber Physical Objects (CPOs) in the context of the Internet of Things (IoT). It covers a wide range of topics related to CPOs, such as resource management, hardware platforms, communication and control, and control and estimation over networks.
