Descriptive model of temporal features of multivariate time series based on granulation

T. Afanasieva, I. Moshkina,

Modern systems are characterized by high rates and volumes of receipt of numerical data. The number of indicators of economical, biological, and technical systems, including Autonomous ones, is increasing, generating large amounts of numerical data of observation in real time. These data have a multidimensional structure and binding to time points, which allows us to consider them in the form of numerical multivariate time series. As part of the descriptive analysis of these data, the article presents new model of representation of local features, considered at different levels of granulation, in respect to temporal features of a multivariate time series in terms of general tendencies. For this purpose, the provisions of the theory of fuzzy sets and fuzzy time series were applied in descriptive model, which provided a linguistic description of tendencies, understandable to the expert. Carried out results in modelling of local feature in terms of tendency in descriptive analysis of COVID-19 spread showed effectiveness and operability of proposed approach. Copyright © 2020 for this paper by its authors.


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  • 1. Version of Record от 2021-08-23


Об авторах
  • T. Afanasieva
    Ulyanovsk State Technical University, Ulyanovsk, Russian Federation
  • I. Moshkina
    Ulyanovsk State Technical University, Ulyanovsk, Russian Federation
Предметная рубрика
  • COVID-19
Название журнала
  • CEUR Workshop Proceedings
  • 2667
  • 287-292
Ключевые слова
  • Data Science; Granulation; Nanotechnology; Real time systems; Time series; Descriptive analysis; Descriptive Model; Fuzzy time series; Linguistic descriptions; Multi-dimensional structure; Multivariate time series; Temporal features; Theory of fuzzy sets; Time series analysis
Тип документа
  • Conference Paper
Тип лицензии Creative Commons
  • CC-BY
Правовой статус документа
  • Свободная лицензия
  • scopus