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The main goal of this article is to decluster Iranian plateau seismic catalog by the epidemic-type aftershock sequence (ETAS) model and compare the results with some older methods. For this purpose, Iranian plateau bounded in 24°–42°N and 43°–66°E is subdivided into three major tectonic zones: (1) North of Iran (2) Zagros (3) East of Iran. The extracted earthquake catalog had a total of 6034 earthquakes (Mw > 4) in the time span 1983–2017. The ETAS model is an accepted stochastic approach for seismic evaluation and declustering earthquake catalogs. However, this model has not yet been used to decluster the seismic catalog of Iran. Until now, traditional methods like the Gardner and Knopoff space–time window method and the Reasenberg link-based method have been used in most studies for declustering Iran earthquake catalog. Finally, the results of declustering by the ETAS model are compared with result of Gardner and Knopoff (Bull Seismol Soc Am 64(5):1363–1367, 1974), Uhrhammer (Earthq Notes 57(1):21, 1986), Gruenthal (pers. comm.) and Reasenberg (Geophys Res 90:5479–5495, 1985) declustering methods. The overall conclusion is difficult, but the results confirm the high ability of the ETAS model for declustering Iranian earthquake catalog. Use of the ETAS model is still in its early steps in Iranian seismological researches, and more parametric studies are needed.
In earthquake occurrence studies, the so-called q value can be considered both as one of the parameters describing the distribution of inter-event times and as an index of non-extensivity. Using simulated datasets, we compare four kinds of estimators, based on principle of maximum entropy (POME), method of moments (MOM), maximum likelihood (MLE), and probability weighted moments (PWM) of the parameters (q and τ0) of the distribution of inter-events times, assumed to be a generalized Pareto distribution (GPD), as defined by Tsallis (1988) in the frame of non-extensive statistical physics. We then propose to use the unbiased version of PWM estimators to compute the q value for the distribution of inter-event times in a realistic earthquake catalogue simulated according to the epidemic type aftershock sequence (ETAS) model. Finally, we use these findings to build a statistical emulator of the q values of ETAS model. We employ treed Gaussian processes to obtain partitions of the parameter space so that the resulting model respects sharp changes in physical behaviour. The emulator is used to understand the joint effects of input parameters on the q value, exploring the relationship between ETAS model formulation and distribution of inter-event times.
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