Simple technique for detection of outliers in one-dimensional numerical data used for point out anomalous consumption
Paper number
1234Conference name
CIRED 2019Conference date
3-6 June 2019Conference location
Madrid, SpainPeer-reviewed
YesMetadata
Show full item recordAuthors
Mantovani Ricci, Davi , Daimon , BrazilBaumann, 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
AIMDate
2019-06-03Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/353http://dx.doi.org/10.34890/581