1. Machine Learning for Cyber Physical Systems
- Author
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Beyerer, Jürgen, Maier, Alexander, and Niggemann, Oliver
- Subjects
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 ,bic Book Industry Communication::T Technology, engineering, agriculture::TH Energy technology & engineering::THR Electrical engineering ,bic Book Industry Communication::T Technology, engineering, agriculture::TJ Electronics & communications engineering::TJK Communications engineering / telecommunications ,bic Book Industry Communication::U Computing & information technology::UT Computer networking & communications - Abstract
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.
- Published
- 2021
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