Iranian Journal of Geophysics

Iranian Journal of Geophysics

Determination of seismic parameters of Iranian earthquakes by network theory

Document Type : Research Article

Authors
1 M.Sc. Student, Department of Physics, Qom Branch, Islamic Azad University, Qom, Iran
2 Associate Professor, Department of Physics, Qom Branch, Islamic Azad University, Qom, Iran,
3 Assistant Professor, Department of Physics, Zanjan University, Zanjan, Iran
Abstract
Complex network theory has appeared as a suitable tool for studying complex phenomena. Earthquakes show spatio-temporal complex behavior that can be studied using complex networks, which enables us to recognize the global properties of Earthquakes.
It is so hard to consider all factors affecting the movement of faults and put them into a compact mathematical equation in order to describe the earthquake phenomenon. In complex network theory, we do not need to know details of the fault system. Using the network method, knowing  the magnitude, time of occurrence and location of seismic events, we are able to understand several aspects of the earthquake phenomenon.
    Studies on earthquakes using the network method are based on how the network is constructed. It was tried to show that the main statistical features of earthquake phenomena in any region can be retrieved from the associated earthquake network.
   In this research, the Baiesi-Paczuski (2004) network model used to investigate the earthquake network.
Earthquake epicenters play the role of network nodes and the relationship between both nodes was established by the relationship defined by Baiesi-Paczuski.
   In this project, by constructing the network, the parameters of seismicity (a-value, b-value), fractal dimension and correlation ratio in the Iran region. In the first attempt we drew out the Gutenberg–Richter law from the earthquakes network and the Omori law from the Baiesi-Paczuski network model.
   We have used data recorded from 1996 to 2020 data at all the broadband and short-period stations of the Iranian Seismological Center.
The results showed that b-value≈ 0.93 and a-value≈6.9  and. Also, the results showed that for df≈1.56  each earthquake with a certain magnitude, the aftershock rates follow the Omori law with the line gradient of p≈-1 and the earthquake degree distribution function in Iran from the power relationship ((P(k)~kγ) with a γ = 1.59. In addition, the distribution function showed that the correlation relation is also a power relationship.
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بابلیان، ا.، 1386، مباحثی در ریاضیات گسسته، انتشارات مبتکران.
 بیت­الهی، ع. و معتمد، پ.، 1389، پارامترهای لرزه­خیزی برای منطقه البرز مرکزی، پژوهشنامه زلزله­شناسی و مهندسی زلزله، سال 13، شماره 3 و 4، 1-8.
رحیم­خانی، پ.، بیت­اللهی، ع.، 1387، پهنه بندی مکانی ضرایب لرزه خیزی b,aدر گستره ایران و مقایسه با ایالتهای لرزه زمین ساختی ایران، دوازدهیمن همایش انجمن زمین‌شناسی ایران، اهواز، شرکت ملی مناطق نفت خیز جنوب.
Abe, S, and Suzuki, N., 2004a, Small-world structure of earthquake network, Physica A Statistical Mechanics and its Applications, 337, 357-362.
Abe, S., and N. Suzuki, 2004b, Scale-free network of earthquakes, Europhysics Letters, 65, 581.
Abe, S., and N. Suzuki, 2005, Scale-invariant statistics of period in directed earthquake network, The European Physical Journal B-Condensed Matter and Complex Systems, 44, 115-117.
 Abe, S., and N. Suzuki, 2006, Complex earthquake networks: Hierarchical organization and assortative mixing, Physical Review E , 74, 026113.
Abe, S., and N. Suzuki, 2007, Dynamical evolution of clustering in complex network of earthquake, The European Physical Journal B, 59, 93-97.
 Abe, S., and N. Suzuki, 2009a, Main shocks and evolution of complex earthquake networks, Brazilian Journal of Physics, 39, 428-430.
 Abe, S., and N. Suzuki, 2009b, Determination of the scale of coarse graining in earthquake networks, Europhysics Letters, 87, 48008.
 Abe, S., D. Pasaten, and N. Suzuki, 2011, Finite data-size scaling of clustering in earthquake
networks, Physica A: Statistical Mechanics and its Applications, 390, 1343-1349.
Allen, M., Jackson, G. and Walker, R., 2004. Late Cenozoic reorganization of the Arabia-Eurasia collision and the comparison of short-term and long-term deformation rates: Tectonics, 23, 0278-7407.
Baiesi, M., and Paczuski, M., 2004, Scale-free networks of earthquakes and aftershocks: Physical Review  E, 69, 066106.
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and Hwang, D.U., 2006, Complex network: structure and dynamics: Physics Reports 424, 175-308.
Caldarelli, G., Scale-free networks, Oxford University Press, 2007.
Costa, L.F., Oliveira O.N.,  Travieso, Jr., G., Ro- drigues, F.A., Boas, P.R.V., Antiqueira, L., Viana , M.P., and da Rocha, L.E.C., 2011, Analyzing and modeling real-world phenomena with complex networks: A survey of applications: Advances in Physics, 60 , 329-412.
Lotfi, N., Darooneh, A. H.,2012, The earthquakes network: the role of cell size,European Physical Journal B, 85, 23-26.
Darooneh, A.H., and Lotfi, N., 2014, Active and passive faults detection by using the PageRank algorithm, Europhysics Letters, 107, 49001.
Davidsen, J., Grassberger, P., Paczuski, M., 2006, Earthquake recurrence as a record breaking process, Geophys. Res. let., 32, 1-4.
Gutenberg, B., and Richter, C.F., 1941, Seismicity of the Earth: Geol. Soc. Am. Bull. 34(1).
Hitara, T., 1989, Fractal Dimension of Fault Systems in Japan: Fractal Structure in Rock Fracture Geometry at Various Scales: Pure and Applied Geophysics, 131, 157-170.
Omori, F., 1984, On the aftershocks of earthquake: Journal of the College of Science, Imperial
 
   of Pattern Informatic and PageRank `s, Bulletin of the Seismological Society of America,
Rezaei, S., Moghaddas, H., Darooneh, A. H., 2019b, PageRank: An alarming index of probable earthquake occurrence, Chaos 29(6).
Telesca, L., and Lovallo, M., 2012, Analysis of seismic sequences by using the method of visibility graph: Europhysics Letters, 97, 50002.
Tenenbaum, J. N., ShlomoHavlin, and H. E. Stanley, 2012, Earthquake networks based on similar
activity patterns, Physical Review. E, 86, 046107. University of Tokyo, 7, 111-120.
Rezaei, S., Moghaddas, H., Darooneh, A. H., Zare, M., 2019a, Forecasting Earthquakes by Hybrid Model.