Skip to main content
Have a personal or library account? Click to login
The Study of Time Series Using the DMA Methods and Geophysical Applications Cover

The Study of Time Series Using the DMA Methods and Geophysical Applications

Open Access
|Dec 2016

Figures & Tables

Figure 1

The scheme of the analysis of a time series using the FL methods.

Figure 2

The global measure of closeness.

Figure 3

The local measure of closeness.

Figure 4

The function under examination.

Figure 5

The measures of activity μDf(t) : a) based on (2), b) based on (3).

Figure 6

Anomalies marked out using the measures of activity (Fig. 5).

Figure 7

The measures of activity μεf(t): a) based on (7), b) based on (8), c) based on (9).

Figure 8

Anomalies marked out using the measures of activity (Fig. 7).

Figure 9

a) Areas of monotoneness (red is for increase, green is for decrease); b) Reduction to the initial record.

Figure 10

A fragment of initial record (Fig. 9): a) Areas of monotoneness (red is for increase, green is for decrease); b) Reduction to the initial record.

Figure 11

The initial time series.

Figure 12

The corresponding activity.

Figure 13

DPS: step 1. Results of identification of anomalies on the indicator of activity.

Figure 14

DPS: step 2. Clustering of the intervals.

Figure 15

DPS: final result. Reduction to the initial function.

Figure 16

The massiveness of anomalies.

Figure 17

Mean activity of the anomalies.

Figure 18

Mean energy of the anomalies.

Figure 19

Mean jaggedness of the anomalies.

Figure 20

Mean scatterness of the anomalies.

Figure 21

Index of anomalies based on massiveness.

Figure 22

Index of anomalies based on mean activity.

Figure 23

Index of anomalies based on mean energy.

Figure 24

Index of anomalies based on mean jaggedness.

Figure 25

Index of anomalies based on mean Scatterness.

Figure 26

Complex index of anomalies.

Figure 27

Anomalies marked out using: a) indLA; b) indOA; c) ind˜A.

Figure 28

Planetary Kp index values for the period from 28.03.2016 to 08.04.2016.

Figure 29

The results of classification of initial data into background (blue), weakly anomalous (green), anomalous (purple) and strongly anomalous (red) fragments using the measure of anomality. On the upper plot the initial record is shown, on the bottom plot the measure of anomality is displayed, calculated for this record.

Language: English
Page range: 16 - 16
Submitted on: Jun 20, 2016
Accepted on: Oct 10, 2016
Published on: Dec 6, 2016
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2016 Sergey Agayan, Shamil Bogoutdinov, Anatoly Soloviev, Roman Sidorov, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.