Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/267187 
Year of Publication: 
2022
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Jahn, Carlos [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New Era. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 33 [ISBN:] 978-3-756541-95-9 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2022 [Pages:] 207-236
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: This publication investigates preliminary data quality analyses to estimate the efforts and expected results of the use of data sets for ML solutions already in the data understanding phase of an implementation. Knowledge about the necessary data cleaning efforts and result qualities allows potentials to be estimated early in the process. Methodology: Through a literature research, characteristics of a time series as well as methods of data cleaning are analysed. Based on the results, a test environment is implemented in Python, enabling the evaluation of individual methods using sample data sets from the process industry and comparing them with different error analyses. Findings: The publication describes a detailed overview of data cleaning procedures and addresses a first Indication of a connection between the final achievable forecast quality and the degree of error of the original data set. Insights into the influence of the choice of preprocessing method on the achievable quality of the AI-based forecast can be concluded. Originality: Within the publication, the link between data characteristics in time series and preprocessing methods is established to draw conclusions in advance about the quality improvement to be expected from selected data cleaning methods and to provide decision support for the selection of the method.
Subjects: 
Artificial Intelligence
Blockchain
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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