Overview
- Includes the full proceedings of the 2016 ML4CPS – Machine Learning for Cyber Physical Systems Conference
- Presents recent and new advances in automated machine learning methods
- Provides an accessible and succinct overview on machine learning for cyber physical systems
- Includes supplementary material: sn.pub/extras
Part of the book series: Technologien für die intelligente Automation (TIA)
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About this book
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016.
Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
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Keywords
Table of contents (8 papers)
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Editors and Affiliations
About the editors
Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.
Prof. Dr. Oliver Niggemann is Professor for Embedded Software Engineering. His research interests are in the field of Distributed Real-time Software and in the fields of analysis and diagnosis of distributed systems. He is a board member of the inIT and a senior researcher at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.
Dr. Christian Kühnert is a senior researcher at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data-driven condition monitoring.
Bibliographic Information
Book Title: Machine Learning for Cyber Physical Systems
Book Subtitle: Selected papers from the International Conference ML4CPS 2016
Editors: Jürgen Beyerer, Oliver Niggemann, Christian Kühnert
Series Title: Technologien für die intelligente Automation
DOI: https://doi.org/10.1007/978-3-662-53806-7
Publisher: Springer Vieweg Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2017
Softcover ISBN: 978-3-662-53805-0Published: 06 December 2016
eBook ISBN: 978-3-662-53806-7Published: 25 November 2016
Series ISSN: 2522-8579
Series E-ISSN: 2522-8587
Edition Number: 1
Number of Pages: VII, 72
Number of Illustrations: 5 b/w illustrations, 19 illustrations in colour
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Knowledge Management