Multifractal detrended fluctuation analysis of ionospheric total electron content data during solar minimum and maximum

Chandrasekhar, E.; Prabhudesai, Sanjana S.; Seemala, G. K.; Shenvi, Nayana

doi:10.1016/j.jastp.2016.09.007

Cited by 30 publications

(11 citation statements)

References 22 publications

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“…Multifractal analysis is an instruments which is used in geophysical studies rather actively (Ramirez-Rojas et al, 2004;Currenti et al, 2005;Ida et al, 2005;Telesca et al, 2005;Chandrasekhar et al, 2016). The multifractality of seismic noise was used for earthquake prediction and seismic hazard assessment in (Lyubushin, 2010;Lyubushin, 2012;Lyubushin, 2013;Lyubushin, 2018;Lyubushin, 2021a).…”

Section: Seismic Noise Statisticsmentioning

confidence: 99%

Investigation of the Global Seismic Noise Properties in Connection to Strong Earthquakes

Lyubushin

2022

Front. Earth Sci.

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The global seismic noise, recorded on a network of 229 broadband seismic stations located around the globe for 25 years, from the beginning of 1997 to the end of 2021, has been investigated. To study the noise properties a set of statistics estimated daily have been used: the multifractal singularity spectrum support width, the minimum entropy of the squared wavelet coefficients, and the wavelet-based Donoho-Johnstone (DJ) index. It is shown that the time points of local extrema of the average values of the analyzed noise properties (minima for singularity spectrum support width and DJ-index and maxima for entropy) tend to occur before strong earthquakes. The time interval from the middle of 2002 to the middle of 2003 is determined, when the trend of decreasing the average coherence of the noise properties in the auxiliary network of 50 reference points changed to an increase. Along with an increase in the average coherence, there is an increase in the radius of the spatial maximum coherences of noise properties. Both of these trends continue until the end of 2021, which is interpreted as a general sign of an increase in the degree of criticality of the state of the planet and, as a result, an increase in global seismic danger. After two mega-earthquakes close in time: 27 February 2010, M=8.8 in Chile and 11 March 2011, M=9.1 in Japan, there was an increase in the spatial scales of the strong coherence of noise parameters, which is a sign of an increase in the critical state. The response of seismic noise properties to variations in the length of the day (LOD) has been studied. An estimate of the correlation function between the mean values of the response to LOD and the logarithm of the released seismic energy in a time window of 1 year indicates a delay in energy release with respect to the maxima of the response of noise properties to LOD with a delay time of about 500 days. In connection with this result, an additional intrigue is the extreme increase in the average value of the response to LOD in 2021.

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Section: Seismic Noise Statisticsmentioning

confidence: 99%

Investigation of the Global Seismic Noise Properties in Connection to Strong Earthquakes

Lyubushin

2022

Front. Earth Sci.

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“…It is widely known that this method is a generalization of the Detrended Fluctuations Analysis (DFA), which examines fractal properties in non-stationary time series [19]. This method is applied with successfully in several areas of science such as: Climatology [20], Biophysics [21], Neurology [22,23], Econophysics [24? ], Macroeconphysics and others [25,26,27,28].…”

Section: Multifractal Detrended Fluctuation Analysis (Mf-dfa)mentioning

confidence: 99%

Multifractal dynamics of COVID-19 vaccines in Europe

Fernandes

Araujo²

2022

Preprint

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This research explores the multifractal dynamics of the daily number of vaccinated time series for COVID-19, considering six European countries (Belgium, Denmark, France, Germany, Greece, and Italy) using the Multifractal Detrended Fluctuations Analysis (MF-DFA). We calculate the multifractal spectrum 𝑓 (𝛼) and apply a fourth-degree polynomial regression fit to estimate the complexity parameters that describe the degree of multifractality of the underlying process. We find that the multifractal dynamics of all these countries are characterized by strongly anti-persistent behaviour or anti-persistent long-term correlations (𝛼 0 < 0.5) a lower degree of multifractality, and small fluctuations are dominant in the multifractal spectrum. Our findings shed light on the period of immunization of the population that adhered to the vaccination campaigns is short and that the application of new doses of vaccines must comply with this phenomenology to keep the people safe.

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“…(3) After splitting the TEC map, the lateral sides of the 600 training images contained a type of artificial image processing noise called wedge effects in image processing because they contained discontinuities (Baert et al, 2014;Lin & Chiou, 2020). A low-pass Butterworth filter (Bianchi and Sorrentino, 2007) was used to reduce the wedge effects for each training image before training the CNN model, because the Butterworth filter was identified as a suitable filter for TEC data and TEC images (Chandrasekhar et al, 2016;Lin & Chiou, 2020).…”

Section: Validation By Two Convolutional Neural Network (Cnn) Modelsmentioning

confidence: 99%

Generalized Two-Dimensional Principal Component Analysis and Two Artificial Neural Networks to Detect Traveling Ionospheric Disturbances Using the Tsunami-Atmosphere-Ionosphere Coupling Mechanism

Lin

2021

Preprint

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A weak tsunami was induced by the 2016 Mw = 7.8 Sumatra earthquake, which occurred at 12:49 on March 2, 2016 (UTC). The epicenter was at 5.060°S, 94.170°E at a depth of 10 km. At 15.02 on March 2 (UTC), the weak tsunami (amplitude: 0.11 m) arrived at the station located at 10.40°S, 105.67°E. The largest first principal eigenvalue derived using the bilateral projection-based two-dimensional principal component analysis (B2DPCA) indicated a spatial traveling ionospheric disturbance (TID), which was caused by internal gravity waves (IGWs), at 13:20 on March 2 (UTC). The largest second principal eigenvalue represented another TID expanding to the southwest. The two largest principal eigenvalues were associated with the TIDs, which were also determined using two back-propagation neural network (BPNN) models and two convolutional neural network (CNN) models, called the BPNN-B2DPCA and CNN-B2DPCA methods, respectively. These two methods yielded the same results as the B2DPCA. Therefore, the robustness and reliability of the B2DPCA were validated.

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Multifractal detrended fluctuation analysis of ionospheric total electron content data during solar minimum and maximum

Cited by 30 publications

References 22 publications

Investigation of the Global Seismic Noise Properties in Connection to Strong Earthquakes

Investigation of the Global Seismic Noise Properties in Connection to Strong Earthquakes

Multifractal dynamics of COVID-19 vaccines in Europe

Generalized Two-Dimensional Principal Component Analysis and Two Artificial Neural Networks to Detect Traveling Ionospheric Disturbances Using the Tsunami-Atmosphere-Ionosphere Coupling Mechanism

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