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© 2017

Machine Learning for Cyber Physical Systems

Selected papers from the International Conference ML4CPS 2016

  • Jürgen Beyerer
  • Oliver Niggemann
  • Christian Kühnert
Conference proceedings

Part of the Technologien für die intelligente Automation book series (TIA)

Table of contents

  1. Front Matter
    Pages I-VII
  2. Alberto Ogbechie, Javier Díaz-Rozo, Pedro Larrañaga, Concha Bielza
    Pages 17-24
  3. Christian Kühnert, Miriam Schleipen, Michael Okon, Robert Henßen, Tino Bischoff
    Pages 25-33
  4. Thomas Bernard, Marc Baruthio, Claude Steinmetz, Jean-Marc Weber
    Pages 35-43
  5. Christian Kühnert, Idel Montalvo Arango
    Pages 45-54
  6. Idel Montalvo Arango, Joaquín Izquierdo Sebastián
    Pages 55-64

About these proceedings

Introduction

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.


The Editors

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. 

Keywords

new approaches in automation Smart Data Analysis Agent Swarm Optimization Industry 4.0 Anomaly Detection in Industrial Networks Big Data Condition Monitoring Data Mining Machine Learning Predictive Maintenance

Editors and affiliations

  • Jürgen Beyerer
    • 1
  • Oliver Niggemann
    • 2
  • Christian Kühnert
    • 3
  1. 1.Institut für Optronik, Systemtechnik und BildauswertungFraunhoferKarlsruheGermany
  2. 2.inIT - Institut für industrielle InformationstechnikHochschule Ostwestfalen-Lippe inITLemgoGermany
  3. 3.MRDFraunhofer IOSB MRDKarlsruheGermany

About the editors

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.   

Bibliographic information

  • Book Title Machine Learning for Cyber Physical Systems
  • Book Subtitle Selected papers from the International Conference ML4CPS 2016
  • Editors Jürgen Beyerer
    Oliver Niggemann
    Christian Kühnert
  • Series Title Technologien für die intelligente Automation
  • Series Abbreviated Title Technologien für die intelligente Automation
  • DOI https://doi.org/10.1007/978-3-662-53806-7
  • Copyright Information Springer-Verlag GmbH Germany 2017
  • Publisher Name Springer Vieweg, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Softcover ISBN 978-3-662-53805-0
  • eBook ISBN 978-3-662-53806-7
  • Edition Number 1
  • Number of Pages VII, 72
  • Number of Illustrations 5 b/w illustrations, 19 illustrations in colour
  • Topics Computational Intelligence
    Data Mining and Knowledge Discovery
    Knowledge Management
  • Buy this book on publisher's site
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