Jetzt sparen: 40% Rabatt auf Titel der Sozialwissenschaften oder ein 30€-Gutschein für Technik eBooks!

Technologien für die intelligente Automation

Machine Learning for Cyber Physical Systems

Selected papers from the International Conference ML4CPS 2016

Herausgeber: Beyerer, Jürgen, Niggemann, Oliver, Kühnert, Christian (Eds.)

Vorschau
  • 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
Weitere Vorteile

Dieses Buch kaufen

eBook n/a
  • ISBN 978-3-662-53806-7
  • Versehen mit digitalem Wasserzeichen, DRM-frei
  • Erhältliche Formate: PDF
  • eBooks sind auf allen Endgeräten nutzbar
Softcover n/a
  • ISBN 978-3-662-53805-0
  • Kostenfreier Versand für Individualkunden weltweit
Über dieses Buch

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.  


Über den Autor

Prof. Dr.-Ing. Jürgen Beyerer is Professor at the  Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.

Prof. Dr. Oliver Niggemann is Professor for Embedded Software Engineering. His research interests are in the field of Distributed Real-time Software and in the fields of analysis and diagnosis of distributed systems. He is a board member of the inIT and a senior researcher at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.

Dr. Christian Kühnert is a senior researcher at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data-driven condition monitoring.   

Stimmen zum Buch

   
   

Inhaltsverzeichnis (8 Kapitel)

Inhaltsverzeichnis (8 Kapitel)
  • A Concept for the Application of Reinforcement Learning in the Optimization of CAM-Generated Tool Paths

    Dripke, Caren (et al.)

    Seiten 1-8

  • Semantic Stream Processing in Dynamic Environments Using Dynamic Stream Selection

    Jacoby, Michael (et al.)

    Seiten 9-15

  • Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment

    Ogbechie, Alberto (et al.)

    Seiten 17-24

  • A Modular Architecture for Smart Data Analysis using AutomationML, OPC-UA and Data-driven Algorithms

    Kühnert, Christian (et al.)

    Seiten 25-33

  • Cloud-based event detection platform for water distribution networks using machine-learning algorithms

    Bernard, Thomas (et al.)

    Seiten 35-43

Dieses Buch kaufen

eBook n/a
  • ISBN 978-3-662-53806-7
  • Versehen mit digitalem Wasserzeichen, DRM-frei
  • Erhältliche Formate: PDF
  • eBooks sind auf allen Endgeräten nutzbar
Softcover n/a
  • ISBN 978-3-662-53805-0
  • Kostenfreier Versand für Individualkunden weltweit
Loading...

Wir empfehlen

Loading...

Bibliografische Information

Bibliographic Information
Buchtitel
Machine Learning for Cyber Physical Systems
Buchuntertitel
Selected papers from the International Conference ML4CPS 2016
Herausgeber
  • Jürgen Beyerer
  • Oliver Niggemann
  • Christian Kühnert
Titel der Buchreihe
Technologien für die intelligente Automation
Buchreihen Band
3
Copyright
2017
Verlag
Springer Vieweg
Copyright Inhaber
Springer-Verlag GmbH Germany
eBook ISBN
978-3-662-53806-7
DOI
10.1007/978-3-662-53806-7
Softcover ISBN
978-3-662-53805-0
Buchreihen ISSN
2522-8579
Auflage
1
Seitenzahl
VII, 72
Anzahl der Bilder
5 schwarz-weiß Abbildungen, 19 Abbildungen in Farbe
Themen