Machine Learning for Cyber Physical Systems
Selected papers from the International Conference ML4CPS 2020
Contributor(s)
Beyerer, Jürgen (editor)
Maier, Alexander (editor)
Niggemann, Oliver (editor)
Language
EnglishAbstract
This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. 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.
Keywords
Cyber-physical systems, IoT; Communications Engineering, Networks; Computer Systems Organization and Communication Networks; Cyber-Physical Systems; Computer Engineering and Networks; Machine Learning; Artificial Intelligence; Cognitive Robotics; Internet of Things; Computational intelligence; Computer-based algorithms; Smart grid; Open Access; Industry 4.0; Electrical engineering; Cybernetics & systems theory; Communications engineering / telecommunications; Computer networking & communicationsDOI
10.1007/978-3-662-62746-4Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
2021Imprint
Springer ViewegSeries
Technologien für die intelligente Automation, 13Classification
Electrical engineering
Communications engineering / telecommunications
Computer networking and communications