The visualization method pipeline for the application to dynamic data analysis
Creators
- 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.
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