Machine Learning for Cyber Physical Systems
Machine Learning for Cyber Physical Systems
Springer | Engineering | December 29, 2016 | ISBN-10: 3662538059 | 72 pages | pdf | 2.87 mb
Springer | Engineering | December 29, 2016 | ISBN-10: 3662538059 | 72 pages | pdf | 2.87 mb
Editors: Beyerer, Jürgen, Niggemann, Oliver, Kühnert, Christian (Eds.)
Selected papers from the International Conference ML4CPS 2016
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
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.
Number of Pages
VII, 72
Number of Illustrations and Tables
5 b/w illustrations, 19 illustrations in colour
Topics
Computational Intelligence
Data Mining and Knowledge Discovery
Knowledge Management
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