Visual Detection of Internal Patterns in the Empirical Data; Communications in Computer and Information Science; Vol. 754 : Creativity in Intelligent Technologies and Data Science

Visual Detection of Internal Patterns in the Empirical Data; Communications in Computer and Information Science; Vol. 754 : Creativity in Intelligent Technologies and Data Science

Bibliographic Details
Parent link:Communications in Computer and Information Science
Vol. 754 : Creativity in Intelligent Technologies and Data Science.— 2017.— [P. 215-230]
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Инженерная школа информационных технологий и робототехники (ИШИТР) Отделение автоматизации и робототехники (ОАР)
Other Authors: Zakharova A. A. Alena Alexandrovna, Vehter E. V. Eugeniya Viktorovna, Shklyar A. V. Aleksey Viktorovich, Zavyalov D. A. Dmitrii Alekseevich
Summary:Title screen
The article proposes the solution of the problem of the multidimensional data research. The purpose of such research is detection of internal regularities in initial data, what increases the level of knowledge and understanding the essence by the researcher. The possibilities of using visual data models to achieve this goals are shown. Results of practical use of visual analysis of multidimensional data for justification of the choice of not determined parameters for modeling and designing oil and gas fields using given analogies. High productivity of the developed approach for solving problems of the multidimensional data analysis was confirmed.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2017
Subjects:
электронный ресурс
труды учёных ТПУ
когнитивная графика
визуализация
системы поддержки принятия решений
интерпретация
визуальные модели
Online Access:https://doi.org/10.1007/978-3-319-65551-2_16
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=657487

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