Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020
Beyerer, Jürgen
Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020 - Springer Nature 2021 - 1 electronic resource (130 p.) - Technologien für die intelligente Automation . - Technologien für die intelligente Automation .
Open Access
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.
Creative Commons
English
9783662627464
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 Electrical engineering Cybernetics & systems theory Communications engineering / telecommunications Computer networking & communications
004.85
Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020 - Springer Nature 2021 - 1 electronic resource (130 p.) - Technologien für die intelligente Automation . - Technologien für die intelligente Automation .
Open Access
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.
Creative Commons
English
9783662627464
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 Electrical engineering Cybernetics & systems theory Communications engineering / telecommunications Computer networking & communications
004.85