Explore
Machine Learning for Cyber-Physical Systems
0 Ungluers have
Faved this Work
Login to Fave
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.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 21 times via unglue.it ebook links.
- 6 - epub (None) at Unglue.it.
- 7 - pdf (None) at Unglue.it.
Keywords
- Automatic validation
- Computer science
- cyber-physical systems
- Machine learning
- Network architecture
- neural networks
- thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPF Information theory::GPFC Cybernetics and systems theory
- thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
- thema EDItEUR::U Computing and Information Technology::UK Computer hardware
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
Links
DOI: 10.1007/978-3-031-47062-2web: https://link.springer.com/book/10.1007/978-3-031-47062-2
Editions
