Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020

• Other Authors: Beyerer, Jürgen (Editor), Maier, Alexander (Editor), Niggemann, Oliver (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Springer Nature 2021
• Series: Technologien für die intelligente Automation 13
• Subjects: Electrical engineering; Communications engineering / telecommunications; Computer networking & communications; 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; Cybernetics & systems theory
• Online Access: OAPEN Library: download the publication; OAPEN Library: description of the publication

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.