Ahmad Zamani; S. Farahi Ghasre Aboonasr
Abstract
The Iranian plateau is one of the active tectonic regions on the earth. Non-uniformly distribution of deformation and repetitive activity of faults have cause a complex pattern of tectonic and seismotectonic activity of Iran. Therefore, in order to study the seismic and geological behaviors of different ...
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The Iranian plateau is one of the active tectonic regions on the earth. Non-uniformly distribution of deformation and repetitive activity of faults have cause a complex pattern of tectonic and seismotectonic activity of Iran. Therefore, in order to study the seismic and geological behaviors of different parts of the country one has to perform tectonic and seismotectonic zoning. Tectonic and seismotectonic zoning of Iran began by conventional methods in the past and developed by numerical zoning in recent years. Conventional methods aren't capable for producing detailed zoning maps. Recently numerical data and statistical and mathematical models have used for produce modern numerical maps. The advantage of numerical pattern recognition is that this method is a powerful tool for objective interpretation of massive of data. Multivariate statistical methods not only apply for tectonic zoning, but also this is useful to reveal the degree of significance and relationship between effective variables on tectonic zoning. In this paper, a large numbers of up-to-date geophysical, seismological, geological and geomorphological data have analyzed by using multivariate statistical methods to produced self-organized numerical tectonic and seismotectonic zoning of Iran. Based on this techniques a seven zoning tectonic and seismotectonic map has constructed for Iran. The role and significance of various parameters have also investigated using ANOVA method. The results indicate that some of the parameters play more important role in self-organized zoning. Based on relationships between parameters, they are been classified into 12 groups. Variables in each group present maximum correlation with each other. It is interesting to note that despite the frequent application of a- and b- values of the Gutenberg Richter magnitude frequency formula, these values show poor correlation with others and do not play a significant role in zoning.
Ahmad Zamani; M. Nedaei
Abstract
One of the basic discussions in geosciences is construction of different tectonic zoning maps. In conventional tectonic zoning, not only the great amounts of subjective judgment are involved but also accurate interpretation of high-dimensional data is so difficult and out of human capability. To alleviate ...
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One of the basic discussions in geosciences is construction of different tectonic zoning maps. In conventional tectonic zoning, not only the great amounts of subjective judgment are involved but also accurate interpretation of high-dimensional data is so difficult and out of human capability. To alleviate these deficiencies, quantitative scientific methods in data mining domain can be applied as an effective and useful tool to construct the new numerical maps in geosciences. In this paper self-organizing map (SOM) neural network that is one of the common methods in data mining has been applied for numerical tectonic zoning of Iran. SOM is an unsupervised artificial neural network particularly adept at pattern recognition and clustering of high-dimensional data. Visualization of high-dimensional data in two-dimensional topological-preserving feature map is another specific capability of SOM that represent both homogeneity within and similarity between clusters. Although there are some similarities between SOM's numerical maps constructed here and the conventional maps but SOM method is more powerful for identification and interpretation of different zones than conventional methods. Utilizing SOM method enables us not only to evaluate the degree of homogeneity in each zone, but also to separate regions zone that experience similar geological evolutionary despite of their geographical locations. For instance Lut and Gavkhuni zones show more homogeneity than Makran and Azerbayejan zones also Kopeh-Dagh and Zagros are located at different regions, they have similar features. The results obtained here represent separation between Makran from EastIranianRanges and Western Azerbaijan from AlborzRanges, too. It is important to recognize that the SOM's results are based purely on the geophysical, geological and seismic features presented previously. So correspondences and differences between the SOM's zones and a given zone based on conventional method must receive careful thought.
A. Zamani; M. Agh-Atabai
Abstract
The 31 March, 2006 earthquake with Mw=6.1 destroyed villages in the Darb-e-Astaneh (Silakhor) region of the Lurestan province. The epicenteral area of this earthquake lies near the Main Recent Fault (MRF) and its right lateral mechanism indicates that it belongs to this fault zone. The main shock was ...
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The 31 March, 2006 earthquake with Mw=6.1 destroyed villages in the Darb-e-Astaneh (Silakhor) region of the Lurestan province. The epicenteral area of this earthquake lies near the Main Recent Fault (MRF) and its right lateral mechanism indicates that it belongs to this fault zone. The main shock was followed by relatively large number of aftershocks. In this research, the aftershock sequence of this earthquake has been studied by measuring quantitative indices of coefficient of variations (CV), the exponent of the power spectral density function, and the generalized multifractal dimensions. The results reveal the presence of fractal structure in the temporal and spatial distribution of aftershock sequence. The multifractal behavior of the aftershock sequence indicates the clustering of the earthquake activity and the degree of the heterogeneity in the seismotectonic and geodynamic processes in the focal region. The results show that the multifractal dimensions of the aftershock sequence decreases and the multifractal dimensions of aftershock epicenters increases with time. It seems that these changes in the multifractal dimensions are related to the activity of secondary and sympathetic faults and changes in the tectonic stress regime of the region. The results also indicate that the multifractal method rather than monofractal approaches is a powerful tool for quantitative analysis of aftershock process's clustering behavior.