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    Simple technique for detection of outliers in one-dimensional numerical data used for point out anomalous consumption

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    CIRED 2019 - 1234.pdf (266.7Kb)
    Paper number
    1234
    Conference name
    CIRED 2019
    Conference date
    3-6 June 2019
    Conference location
    Madrid, Spain
    Peer-reviewed
    Yes
    Metadata
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    Authors
    Mantovani Ricci, Davi , Daimon , Brazil
    Baumann, Paulo Henrique , Daimon , Brazil
    Romero, Fabio , Daimon , Brazil
    MEFFE, ANDRÉ, DAIMON ENGENHARIA E SISTEMAS, Brazil
    H. S. G. Jesus, Armando , CEMAR, Brazil
    S. Oliveira, Eliezer , CEMAR, Brazil
    A. Pinheiro , Lucas, CEMAR, Brazil
    Abstract
    This paper presents a simple technique for detection of outliers in one-dimensional numerical data. This was developed to point out anomaly in the consumption information in the DSO’s database. This, in turn, was inspired from concepts like DBSCAN and K-Means grouping techniques. It has been shown plausible for data whose distribution curve is skewed, positively or negatively.
    Publisher
    AIM
    Date
    2019-06-03
    Published in
    • CIRED 2019 Conference
    Permanent link to this record
    https://cired-repository.org/handle/20.500.12455/353
    http://dx.doi.org/10.34890/581
    ISSN
    2032-9644
    ISBN
    978-2-9602415-0-1

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