Published 2019 | Version v1
Miscellaneous

The visualization method pipeline for the application to dynamic data analysis

  • 1. National Research Nuclear University MEPhI, Moscow (Russian Federation)

Description

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 economical data based on visualization method.

Part of:
27th International Symposium on Nuclear Electronics and Computing (NEC'2019). Book of Abstracts

Additional details

Publishing Information

Publisher
JINR
Imprint Place
Dubna (Russian Federation)
Imprint Title
27th International Symposium on Nuclear Electronics and Computing (NEC'2019). Book of Abstracts
Imprint Pagination
152 p.
Journal Page Range
p. 141
Report number
INIS-XJ--001

Conference

Title
27. international symposium on nuclear electronics and computing
Acronym
NEC 2019
Dates
30 Sep - 4 Oct 2019
Place
Budva, Becici (Montenegro)

INIS

Country of Publication
Joint Institute for Nuclear Research (JINR)
Country of Input or Organization
Joint Institute for Nuclear Research (JINR)
INIS RN
51015833
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; DATA VISUALIZATION; MATHEMATICAL MODELS
Descriptors DEC
DATA ANALYSIS; DATA PROCESSING; MATHEMATICAL LOGIC; PROCESSING

Optional Information

Notes
Submitted to CEUR Workshop Proceedings