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.


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    Title :

    Outlier Treatment for Institutional Smart Meter Dataset


    Contributors:


    Publication date :

    2022-12-01


    Size :

    658435 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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