Time Series Classification Based on Visualization of Recurrence Plots

Кіріченко, Л. О.; Зінченко, П. П.

Публікація:
Time Series Classification Based on Visualization of Recurrence Plots

dc.contributor.author	Кіріченко, Л. О.
dc.contributor.author	Зінченко, П. П.
dc.date.accessioned	2021-06-10T20:16:52Z
dc.date.available	2021-06-10T20:16:52Z
dc.date.issued	2021
dc.description.abstract	Ordered data sets such as time series are found in almost all areas of human activity from cardiograms and to cyberattacks. Classification of time series is one of the most difficult tasks in data mining. In the article, a new method of time series classification based on the construction of recurrence plots is considered. The time series is ransformed into a matrix, which characterizes the recurrence of the time series states, and the matrix is presented as a black-and-white image. Further, the convolutional neural network is used to classify the image. The application of the method is demonstrated by examples of simulated time series. A comparative analysis of the classification of noisy time series is carried out. The dependences of the classification accuracy on the noise level of time series are obtained. The results showed that the considered method has a high enough classification accuracy at high noise levels.	uk_UA
dc.identifier.citation	Kirichenko L. Time Series Classification Based on Visualization of Recurrence Plots / L. Kirichenko, P. Zinchenko // Communications in Computer and Information Science. – 2021. – P. 101–108.	uk_UA
dc.identifier.uri	https://openarchive.nure.ua/handle/document/16445
dc.language.iso	en	uk_UA
dc.publisher	CCIS	uk_UA
dc.subject	Time series	uk_UA
dc.subject	noise	uk_UA
dc.subject	classification	uk_UA
dc.subject	recurrence plot	uk_UA
dc.subject	convolutional neural networks (CNN)	uk_UA
dc.title	Time Series Classification Based on Visualization of Recurrence Plots	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication