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

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Paper number
1234
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
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.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
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