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Book
Data-driven Methods for Fault Localization in Process Technology
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ISBN: 1000036427 3731500981 Year: 2013 Publisher: KIT Scientific Publishing

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Control systems at production plants consist of a large number of process variables. When detecting abnormal behavior, these variables generate an alarm. Due to the interconnection of the plant's devices the fault can lead to an alarm flood. This again hides the original location of the causing device. In this work several data-driven approaches for root cause localization are proposed, compared and combined. All methods analyze disturbed process data for backtracking the propagation path.


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De letalitate vvlnervm et inspectione cadaveris post occisvm hominem ...
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Year: 1763 Publisher: Lipsiae : ex officina Langenhemia,

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Die vertragliche Aufklärungspflicht des Arztes : insbesondere bei der Anwendung und Verschreibung von Arzneimitteln
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ISBN: 3883392812 Year: 1982 Publisher: Bochum Brockmeyer

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Book
Zur Stratigraphie und Tektonik des mittleren Ammergebirges
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Year: 1964 Publisher: Berlin Druck

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Erläuterungen zur geologischen Karte von Bayern : Oberammergau
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Year: 1967 Publisher: München : Bayerische geologisches Landesamt,

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Erläuterungen zur geologischen Karte von Bayern : Linderhof
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Year: 1967 Publisher: München : Bayerische geologisches Landesamt,

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Book
Machine Learning for Cyber Physical Systems
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ISBN: 3662538059 3662538067 Year: 2017 Publisher: Springer Berlin Heidelberg

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Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2018
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ISBN: 3662584859 3662584840 Year: 2019 Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer Vieweg,

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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. 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. Dr. ChristianKühnert 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. Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.


Book
Erläuterungen zur geologischen Karte von Bayern : Bayersoien
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Year: 1969 Publisher: München : Bayerische geologisches Landesamt,

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Erläuterungen zur geologischen Karte von Bayern : Rosshaupten
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Year: 1974 Publisher: München : Bayerische geologisches Landesamt,

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