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000866112 1001_ $$0P:(DE-HGF)0$$aFerdowsi, Mohsen$$b0
000866112 245__ $$aMeasurement Selection for Data-Driven Monitoring of Distribution Systems
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000866112 520__ $$aThis article investigates the problem of measurement selection for data-driven monitoring approaches. Several approaches to input variable selection (IVS) are analyzed, and a general procedure for finding the optimal order for the selection of candidate measurements is presented. The method is based on the extensions of partial correlation and minimal redundancy maximum relevance criteria to support IVS problems involving multiple outputs. This method can be used to find the minimal set of measurements for achieving a target estimation accuracy. The results demonstrate the advantages and limits of the introduced method in comparison to the other approaches discussed in this article.
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000866112 7001_ $$0P:(DE-Juel1)179029$$aBenigni, Andrea$$b1$$eCorresponding author
000866112 7001_ $$0P:(DE-HGF)0$$aMonti, Antonello$$b2
000866112 7001_ $$0P:(DE-HGF)0$$aPonci, Ferdinanda$$b3
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