Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020

• Kolejni autorzy: Beyerer, Jürgen (Redaktor), Maier, Alexander (Redaktor), Niggemann, Oliver (Redaktor)
• Format: Elektroniczne Rozdział
• Język: angielski
• Wydane: Springer Nature 2021
• Seria: Technologien für die intelligente Automation
• Hasła przedmiotowe: Electrical engineering; Communications engineering / telecommunications; Computer networking & communications; Cyber-physical systems, IoT; Communications Engineering, Networks; Computer Systems Organization and Communication Networks; Cyber-Physical Systems; Computer Engineering and Networks; Machine Learning; Artificial Intelligence; Cognitive Robotics; Internet of Things; Computational intelligence; Computer-based algorithms; Smart grid; Open Access; Industry 4.0; Cybernetics & systems theory
• Dostęp online: DOAB: download the publication; DOAB: description of the publication

Streszczenie

This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. 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.

Opis fizyczny

1 electronic resource (130 p.)

ISBN

978-3-662-62746-4

Ograniczenie dostępu

Open Access