Open AccessA Suggested method for detecting outliers based on a particle swarm optimization algorithm
Author(s) -
Emad Obaid Merza,
Nashaat Jasim Al-Anber
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1897/1/012021
Subject(s) - outlier , particle swarm optimization , computer science , algorithm , field (mathematics) , data mining , distribution (mathematics) , mathematical optimization , artificial intelligence , mathematics , pure mathematics , mathematical analysis
The occurrence of tremendous developments in the field of data has led to the formation of huge volumes of data, and it is natural that this leads to the presence of outliers in this data for many reasons. The presence of outliers in the data affects the statistical analysis, so we must try to reduce their impact in various ways. On the other hand, the existence of outliers may be of great benefit in many application and of great importance in various fields. In this paper we propose a new method for detecting outliers based on the Particle Swarm Optimization algorithm (PSO). The new propose algorithm was compared with the normal distribution method, and the results obtained from the new method were very promising and encouraging.