Time Series Analysis by Fuzzy Logic Methods-Reference-Cited by-同舟云学术

Time Series Analysis by Fuzzy Logic Methods

Published:2023-05-03 Issue:5 Volume:16 Page:238
ISSN:1999-4893
Container-title:Algorithms
language:en
Short-container-title:Algorithms

Author:

Agayan Sergey M.¹^ORCID,Kamaev Dmitriy A.²,Bogoutdinov Shamil R.¹³,Aleksanyan Andron O.⁴,Dzeranov Boris V.¹^ORCID

Affiliation:

1. Geophysical Center of the Russian Academy of Sciences, 119296 Moscow, Russia

2. Research and Production Association “Typhoon”, 249038 Obninsk, Russia

3. Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences, 123995 Moscow, Russia

4. Obninsk Institute for Nuclear Power Engineering, 249040 Obninsk, Russia

Abstract

The method of analyzing data known as Discrete Mathematical Analysis (DMA) incorporates fuzzy mathematics and logic. This paper focuses on applying DMA to study the morphology of time series by utilizing the language of fuzzy mathematics. The morphological characteristics of the time series, such as background, slopes, and vertices, are considered fuzzy sets within the domain of its definition. This allows for the use of fuzzy logic in examining the morphology of time series, ultimately leading to the detection of anomalies.

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Link

https://www.mdpi.com/1999-4893/16/5/238/pdf

Reference26 articles.

1. Gvishiani, A., and Soloviev, A. (2020). Observations, Modeling and Systems Analysis in Geomagnetic Data Interpretation, Springer International Publishing.

2. Short introduction into DMA;Agayan;Russ. J. Earth Sci.,2018

3. Mathematical methods of geoinformatics. III. Fuzzy comparisons and recognition of anomalies in time series;Gvishiani;Cybern. Syst. Anal.,2008