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Baum, Marcus
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Baum, Marcus
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Baum, Marcus
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Baum, M.
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2018Journal Article Editorial Contribution (Editorial, Introduction, Epilogue) [["dc.bibliographiccitation.firstpage","1124"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","IEEE Transactions on Industrial Informatics"],["dc.bibliographiccitation.lastpage","1126"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Hanebeck, Uwe"],["dc.contributor.author","Baum, Marcus"],["dc.contributor.author","Huber, Marco F."],["dc.date.accessioned","2020-12-10T18:26:17Z"],["dc.date.available","2020-12-10T18:26:17Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1109/TII.2018.2797956"],["dc.identifier.eissn","1941-0050"],["dc.identifier.issn","1551-3203"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76027"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Guest Editorial Special Section on Multisensor Fusion and Integration for Intelligent Systems"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","editorial_ja"],["dspace.entity.type","Publication"]]Details DOI2018Journal Article [["dc.bibliographiccitation.firstpage","14"],["dc.bibliographiccitation.journal","Automatica"],["dc.bibliographiccitation.lastpage","19"],["dc.bibliographiccitation.volume","98"],["dc.contributor.author","Huber, Marco F."],["dc.contributor.author","Zöller, Marc-André"],["dc.contributor.author","Baum, Marcus"],["dc.date.accessioned","2019-07-29T12:22:30Z"],["dc.date.available","2019-07-29T12:22:30Z"],["dc.date.issued","2018"],["dc.description.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."],["dc.identifier.doi","10.1016/j.automatica.2018.08.025"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62137"],["dc.language.iso","en"],["dc.relation.issn","0005-1098"],["dc.title","Linear programming based time lag identification in event sequences"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]Details DOI