NDLI: An approach for increasing the level of accuracy in Supply Chain simulation by using patterns on input data

Content Provider	IEEE Xplore Digital Library
Author	Rabe, Markus Scheidler, Anne Antonia
Copyright Year	2014
Description	Author affiliation: Technical University Dortmund, Leonhard-Euler-Straße 5, 44227, GERMANY (Rabe, Markus; Scheidler, Anne Antonia)
Abstract	Setting up simulation scenarios in the field of Supply Chains (SCs) is a big challenge because complex input data must be specified and careful input data management as well as precise model design are necessary. SC simulation needs a large amount of input data - especially in times of big data, in which the data is often approximated by statistical distributions from real world observations. This paper deals with the question how the model itself and its input can be effectively complemented. This takes into account the commonly known fact, that the accuracy of a model output depends on the model input. Therefore an approach for using techniques of Knowledge Discovery in Databases is introduced to derive logical relations from the data. We discuss how Knowledge Discovery would be applied, as a preprocessing step for simulation scenario setups, in order to provide benefits for the level of accuracy in simulation models.
Starting Page	1897
Ending Page	1906
File Size	305818
Page Count	10
File Format	PDF
e-ISBN	9781479974863
DOI	10.1109/WSC.2014.7020037
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Accuracy Adaptation models Analytical models Computational modeling Standards Knowledge discovery
Content Type	Text
Resource Type	Article

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