Linear programming based time lag identification in event sequences

2018 | journal article. A publication with affiliation to the University of Göttingen.

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​Linear programming based time lag identification in event sequences​
Huber, M. F.; Zöller, M.-A. & Baum, M. ​ (2018) 
Automatica98 pp. 14​-19​.​ DOI: https://doi.org/10.1016/j.automatica.2018.08.025 

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Authors
Huber, Marco F.; Zöller, Marc-André; Baum, Marcus 
Abstract
Many technical systems like manufacturing plants or software applications generate large event sequences. Knowing the temporal relationship between events is important for gaining insights into the status and behavior of the system. This paper proposes a novel approach for identifying the time lag between different event types. This identification task is formulated as a binary integer optimization problem that can be solved efficiently and close to optimality by means of a linear programming approximation. The performance of the proposed approach is demonstrated on synthetic and real-world event sequences.
Issue Date
2018
Journal
Automatica 
Organization
Institut für Informatik 
ISSN
0005-1098
Language
English

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