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Advanced water management

  • Thomas Rauschenbach

    Prof. Dr.-Ing. habil. Thomas Rauschenbach studied electrical engineering at the Technical University of Ilmenau. He obtained his doctorate in 1998 and his habilitation in 2004. Since 2007, he has been director of the Ilmenau branch of the Fraunhofer IOSB Applied Systems Technology (AST). In 2011, Thomas Rauschenbach was appointed Honorary Professor for Modelling, Prediction and Diagnosis of Technical Systems at the Technical University of Ilmenau. Since 2018 has been the spokesman of the Fraunhofer Water Systems Alliance.

     EMAIL logo     und Jürgen Moßgraber

    Dr.-Ing. Jürgen Moßgraber studied Computer Science at the University of Karlsruhe, Germany, from 1992 to 1997, specializing in system architecture and environmental information systems. He received a PhD from the Karlsruhe Institute of Technology, Germany in 2016. His research interests include the design and implementation of web-based information systems with state-of-the-art technologies. He has particular experience with the design of distributed systems handling large-scale databases and modern architectures for task-oriented systems with a service- and event-based approach.
Veröffentlicht/Copyright: 25. Juni 2024
at - Automatisierungstechnik
Aus der Zeitschrift at - Automatisierungstechnik Band 72 Heft 6

Published Online: 2024-06-25
Published in Print: 2024-06-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Advanced water management
  4. Survey
  5. Advances in dissolved oxygen prediction and control methods in aquaculture: a review
  6. Methods
  7. Probabilistic multi-step ahead streamflow forecast based on deep learning
  8. A new assessment method on co-occurring mountain and plain floods based on copula functions
  9. Application
  10. Prescriptive analytics for low and high water management in German waterways
  11. Tools
  12. Integration of selected AI methods into a simulation tool for urban wastewater systems – towards practical application
  13. NiMo 4.0 – Enabling advanced data analytics with AI for environmental governance in the water domain
https://doi.org/10.1515/auto-2024-0060

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Advanced water management
  4. Survey
  5. Advances in dissolved oxygen prediction and control methods in aquaculture: a review
  6. Methods
  7. Probabilistic multi-step ahead streamflow forecast based on deep learning
  8. A new assessment method on co-occurring mountain and plain floods based on copula functions
  9. Application
  10. Prescriptive analytics for low and high water management in German waterways
  11. Tools
  12. Integration of selected AI methods into a simulation tool for urban wastewater systems – towards practical application
  13. NiMo 4.0 – Enabling advanced data analytics with AI for environmental governance in the water domain
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© 2025 De Gruyter Brill
Heruntergeladen am 11.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/auto-2024-0060/html
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