This paper shows how outlier treatment is performed on an institutional smart meter dataset. Smart meters are installed in the institution to record energy consumed in as pecific lab for every minute, and it is taken as in put. By using the desired method, outliers are removed from the input dataset. And the removed outliers are filled by certain fill methods. Their performance is measured by using Mean Absolute Deviation and Receiver Operating Characteristics. The obtained results are collectively compared to determine a method with good accuracy and a threshold value.
Outlier Treatment for Institutional Smart Meter Dataset
01.12.2022
658435 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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