This paper is devoted to visualization of multidimensional fuzzy series and describes analysis methodology based on images that can be built after the initial time series transformation. It is shown that the most rigid structure of a fuzzy number is the number of components with the highest value of membership function. Built in accordance with the proposed method a series of visual images reflect the tendency of the fuzzy time series. The application of fuzzy time series visualization facilitates the identification of high-quality bonds in the consideration of dynamical semi-system (including social and economic). The proposed approach allows a qualitative level to solve the problem of grouping, structuring and forecasting in such systems, but there are doubts in numerical accuracy and quality.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 10 Nov 2020|
|Event||2020 International Conference on Information Technology in Business and Industry, ITBI 2020 - Novosibirsk, Russian Federation|
Duration: 6 Apr 2020 → 8 Apr 2020
ASJC Scopus subject areas
- Physics and Astronomy(all)