Publication:
The visualization method pipeline for the application to dynamic data analysis

Простая страница элемента
dc.contributor.authorPopov, D.
dc.contributor.authorGrigorieva, M.
dc.contributor.authorGalkin, T.
dc.contributor.authorPilyugin, V.
dc.contributor.authorПилюгин, Виктор Васильевич
dc.date.accessioned2024-11-21T16:58:46Z
dc.date.available2024-11-21T16:58:46Z
dc.date.issued2019
dc.description.abstractCopyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).The new era of scientific research brings an enormous amount of data for scientists. These complex and multidimensional data structures are used for the verification of scientific hypothesis. Exploring such data by researchers requires the development of new technologies for its efficient processing, investigation and interpretation. Intellectual data analysis and statistical methods are rapidly developing, and this is where visualization methods are getting their place. This work describes mathematical basis of the developed visualization tool for the analysis of multidimensional dynamic data. This tool provides the pipeline of methods, which combined, allow to cope with a set of practical tasks (anomalies detection, cluster, trends and variation analysis) using visualization method. Authors provided mathematical models of geometrical operations under the data domain, algorithms for solving the mentioned classes of tasks and several use-cases with technological and economic data based on visualization method.
dc.format.extentС. 295-299
dc.identifier.citationThe visualization method pipeline for the application to dynamic data analysis / Popov, D. [et al.] // CEUR Workshop Proceedings. - 2019. - 2507. - P. 295-299
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85077572614&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/19259
dc.relation.ispartofCEUR Workshop Proceedings
dc.titleThe visualization method pipeline for the application to dynamic data analysis
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume2507
relation.isAuthorOfPublication587dcc86-4e67-42b0-9b95-3cabd75653c4
relation.isAuthorOfPublication.latestForDiscovery587dcc86-4e67-42b0-9b95-3cabd75653c4
relation.isOrgUnitOfPublication010157d0-1f75-46b2-ab5b-712e3424b4f5
relation.isOrgUnitOfPublication.latestForDiscovery010157d0-1f75-46b2-ab5b-712e3424b4f5
Файлы
Коллекции
Публикации