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Data Mining mit Prozessdaten (Data Mining with Process Data)

Authors: Andreas Schuppert; Rainer Perne;

Data Mining mit Prozessdaten (Data Mining with Process Data)

Abstract

Abstract Durch die zunehmende Komplexität der Produktionsprozesse in innovativen Anwendungsfeldern wird die Prozessanalyse und -Modellierung vor neue Herausforderungen gestellt. Typische Problemfelder sind reaktive Feststoffprozesse, komplexe Polymerisationsprozesse und insbesondere biotechnologische Prozesse. Zur Analyse solcher extrem komplexer Systeme sind spezialisierte Verfahren verfügbar, die unter dem Sammelbegriff „Data Mining“ subsummiert werden. Sie erlauben eine zuverlässige Extraktion auch komplexer Muster mit hohem Informationsgehalt aus unstrukturierten Daten. Die für die Prozessanalyse relevanten softwaretechnischen und methodischen Aspekte des Data Mining werden diskutiert und entsprechende Anwendungsworkflows exemplarisch am Beispiel eines biotechnischen Produktionsprozesses sowie eines Polymerprozesses demonstriert.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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