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      Multifractal analysis of temporal and spatial characteristics of earthquakes in Eurasian seismic belt

      1 , 1 , 1 , 1 , 2 , 3 , 4
      Open Geosciences
      Walter de Gruyter GmbH

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          Abstract

          Seismic activity has complexity and randomness, and its temporal and spatial distribution has complexity, stage, level, and inheritance. The study of the temporal and spatial distribution characteristics of seismic activity is of great significance to the understanding of the law of seismic activity, such as the law that the time series of seismicity in the seismic belt is consistent with the complexity of geographical structure, the prediction of seismic risk, and other research related to earthquake. This article selects the seismic data catalog of the whole Eurasian seismic belt as the research object. Based on the characteristics of the seismic geological environment and tectonic environment characteristics, the multifractal analysis method is used for the seismic data of the seismic activity directory. The results show that the seismic activity of seismic zones has obvious multifractal structure of complex in time series and spatial scales, which can well reveal the seismic characteristics of seismic activity in time and space. In terms of time series, the study area D decreases significantly with time and energy before the occurrence of a large earthquake, and the time series of seismic activity in the study area is highly complex and highly correlated with the geological structure. Spatially, the spatial distribution of seismic intensity in the study area is infinite and sparse, showing the characteristics of infinite clustering. Therefore, it can reveal the basic rule of seismic activity effectively and lay a certain theoretical foundation for earthquake prevention and control in this seismic zone.

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          • Record: found
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          Multiple-Group Factor Analysis Alignment

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            • Record: found
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            Roughness of natural fault surfaces

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              • Record: found
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              • Article: not found

              Natural time analysis of critical phenomena.

              A quantity exists by which one can identify the approach of a dynamical system to the state of criticality, which is hard to identify otherwise. This quantity is the variance κ(1)(≡ - (2)) of natural time χ, where = Σp(k)f(χ(k)) and p(k) is the normalized energy released during the kth event of which the natural time is defined as χ(k) = k/N and N stands for the total number of events. Then we show that κ(1) becomes equal to 0.070 at the critical state for a variety of dynamical systems. This holds for criticality models such as 2D Ising and the Bak-Tang-Wiesenfeld sandpile, which is the standard example of self-organized criticality. This condition of κ(1) = 0.070 holds for experimental results of critical phenomena such as growth of rice piles, seismic electric signals, and the subsequent seismicity before the associated main shock.
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                Author and article information

                Journal
                Open Geosciences
                Walter de Gruyter GmbH
                2391-5447
                June 07 2023
                June 07 2023
                January 01 2023
                June 07 2023
                June 07 2023
                January 01 2023
                : 15
                : 1
                Affiliations
                [1 ]School of Life Science, Shaoxing University , Shaoxing , 312000 China
                [2 ]School of Public Affairs and Administration, University of Electronic Science and Technology of China , Chengdu , 610054 China
                [3 ]Department of Geography and Anthropology, Louisiana State University , Baton Rouge , LA 70803 , United States
                [4 ]School of Automation, University of Electronic Science and Technology of China , Chengdu , 610054 , China
                Article
                10.1515/geo-2022-0482
                a6e612e6-0abb-4c2c-adec-89ea68613bcc
                © 2023

                http://creativecommons.org/licenses/by/4.0

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