Machine Learning for Cyber-Physical Systems
Selected papers from the International Conference ML4CPS 2023
Contributor(s)
Niggemann, Oliver (editor)
Krantz, Maria (editor)
Kühnert, Christian (editor)
Language
EnglishAbstract
This open access proceedings 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 Hamburg (Germany), March 29th to 31st, 2023. 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. This is an open access book.
Keywords
Cyber-physical systems; Neural networks; Computer Science; Network architecture; Automatic validation; Machine learningDOI
10.1007/978-3-031-47062-2ISBN
9783031470622, 9783031470615, 9783031470622Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
Cham, 2024Imprint
Springer Nature SwitzerlandSeries
Technologien für die intelligente Automation, 18Classification
Electronics engineering
Cybernetics and systems theory
Computer hardware
Artificial intelligence
Mathematical modelling