Substation Signal Matching with a Bagged Token Classifier

Currently, engineers at substation service providers match customer data with the corresponding internally used signal names manually. This paper proposes a machine learning method to automate this process based on substation signal mapping data from a repository of executed projects. To this end, a...

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Bibliographic Details
Published inRecent Trends and Future Technology in Applied Intelligence pp. 372 - 380
Main Authors Wang, Qin, Schönborn, Sandro, Pignolet, Yvonne-Anne, Widmer, Theo, Franke, Carsten
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
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Summary:Currently, engineers at substation service providers match customer data with the corresponding internally used signal names manually. This paper proposes a machine learning method to automate this process based on substation signal mapping data from a repository of executed projects. To this end, a bagged token classifier is proposed, letting words (tokens) in the customer signal name vote for provider signal names. In our evaluation, the proposed method exhibits better performance in terms of both accuracy and efficiency over standard classifiers.
ISBN:331992057X
9783319920573
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-92058-0_36