Machine Learning for Cyber Physical Systems -

Machine Learning for Cyber Physical Systems

Selected papers from the International Conference ML4CPS 2016
Buch | Softcover
VII, 72 Seiten
2016 | 1st ed. 2017
Springer Berlin (Verlag)
978-3-662-53805-0 (ISBN)
181,89 inkl. MwSt

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.  


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.

A Concept for the Application of Reinforcement Learning in the Optimization of CAM-Generated Tool Paths.- Semantic Stream Processing in Dynamic Environments Using Dynamic Stream Selection.- Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment.- A Modular Architecture for Smart Data Analysis using AutomationML, OPC-UA and Data-driven Algorithms.- Cloud-based event detection platform for water distribution networks using machine-learning algorithms.- A Generic Data Fusion and Analysis Platform for Cyber-Physical Systems.- Agent Swarm Optimization: Exploding the search space.- Anomaly Detection in Industrial Networks using Machine Learning.  

   

Erscheinungsdatum
Reihe/Serie Technologien für die intelligente Automation
Zusatzinfo VII, 72 p. 24 illus., 19 illus. in color.
Verlagsort Berlin
Sprache englisch
Maße 168 x 240 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Wirtschaft Betriebswirtschaft / Management Unternehmensführung / Management
Schlagworte Agent Swarm Optimization • Anomaly Detection in Industrial Networks • Artificial Intelligence • Big Data • Computational Intelligence • Condition Monitoring • Data Mining • data mining and knowledge discovery • Engineering • Engineering: general • Expert systems / knowledge-based systems • Industry 4.0 • knowledge management • machine learning • new approaches in automation • Predictive Maintenance • Smart Data Analysis
ISBN-10 3-662-53805-9 / 3662538059
ISBN-13 978-3-662-53805-0 / 9783662538050
Zustand Neuware
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