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100 1 _ |a Ferdowsi, Mohsen
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245 _ _ |a Measurement Selection for Data-Driven Monitoring of Distribution Systems
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520 _ _ |a This article investigates the problem of measurement selection for data-driven monitoring approaches. Several approaches to input variable selection (IVS) are analyzed, and a general procedure for finding the optimal order for the selection of candidate measurements is presented. The method is based on the extensions of partial correlation and minimal redundancy maximum relevance criteria to support IVS problems involving multiple outputs. This method can be used to find the minimal set of measurements for achieving a target estimation accuracy. The results demonstrate the advantages and limits of the introduced method in comparison to the other approaches discussed in this article.
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700 1 _ |a Benigni, Andrea
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700 1 _ |a Monti, Antonello
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700 1 _ |a Ponci, Ferdinanda
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