Запис Детальніше

Comparative Analysis of Noisy Time Series Clustering

Електронного архіву Харківського національного університету радіоелектроніки (Open Access Repository of KHNURE)

Переглянути архів Інформація
 
 
Поле Співвідношення
 
Title Comparative Analysis of Noisy Time Series Clustering
 
Creator Кіріченко, Л. О.
Радівілова, Т. А.
Ткаченко, А. Є.
 
Subject Time Series Clustering
DBSCAN Method
Atypical Time Series
Noisy Time Series Clustering
 
Description A comparative analysis of the clustering of sample time series was
performed. The clustering sample contained time series of various types, among
which atypical objects were present. In the numerical experiment, white noise
with different variance was added to the time series. Clustering was performed
by k-means and DBSCAN methods using various similarity functions of time
series. The values of the quality functionals were quantitative measures of the
quality of clustering. The best results were shown by the DBSCAN method using the Euclidean metric with a Complexity Invariant Distance. The method allows to separate a cluster with atypical series at different levels of additive
noise. The results of the clustering of real time series confirmed the applicability of the DBSCAN method for detecting anomaly.
 
Date 2019-06-19T08:52:30Z
2019-06-19T08:52:30Z
2019
 
Type Thesis
 
Identifier Kirichenko L. Comparative Analysis of Noisy Time Series Clustering / L. Kirichenko L., T. Radivilova, A. Tkachenko // Computational Linguistics and Intelligent Systems : proceedings of the 3rd International Conference, April 18-19, 2019. – Kharkiv, 2019. – Volume I. – P.84-196.
http://openarchive.nure.ua/handle/document/9456
 
Language en