Machine learning for cyber physical systems : selected papers from the international conference ML4CPS 2018 / Jürgen Beyerer, [and 2 others], editors.
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 Karlsruhe, October 23-24, 2018. Cyb...
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| Online Access: |
Full Text (via Springer) |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Germany :
Springer Vieweg,
[2019]
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| Series: | Technologien für die intelligente Automation : technologies for intelligent automation ;
Band 9. |
| Subjects: |
Table of Contents:
- Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Project
- Deduction of time-dependent machine tool characteristics by fuzzy-clustering
- Unsupervised Anomaly Detection in Production Lines
- A Random Forest Based Classifer for Error Prediction of Highly Individualized Products
- Web-based Machine Learning Platform for Condition-Monitoring
- Selection and Application of Machine Learning-Algorithms in Production Quality
- Which deep artifificial neural network architecture to use for anomaly detection in Mobile Robots kinematic data
- GPU GEMM-Kernel Autotuning for scalable machine learners
- Process Control in a Press Hardening Production Line with Numerous Process Variables and Quality Criteria
- A Process Model for Enhancing Digital Assistance in Knowledge-Based Maintenance
- Detection of Directed Connectivities in Dynamic Systems for Different Excitation Signals using Spectral Granger Causality
- Enabling Self-Diagnosis of Automation Devices through Industrial Analytics
- Making Industrial Analytics work for Factory Automation Applications
- Application of Reinforcement Learning in Production Planning and Control of Cyber Physical Production Systems
- LoRaWan for Smarter Management of Water Network: From metering to data analysis.