- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
We study the spatio-temporal characteristics of earthquakes, and find that power laws and allometric growth laws are both statistically significant in the seismic dataset. For further analyzing the complexity of earthquake sequence, an approach of weighted earthquake networks modeling is presented with using the seismic and rock mass datasets. The rock masses covering the entire region are used to divide the region into a lot of small areas. It is shown that the distributions of connectivities and link weights both follow power law decay forms. The discovery of allometric growth laws is important for studying the dynamics of massive earthquakes. The suggested earthquake network is helpful to study the interactions between rock masses and expand a research prototype for modeling seismicity on complex networks.
Studying the spatio-temporal dynamics of earthquakes is one of the most significant subjects in seismic research field. Complex network provides a useful technique to mine the spatio-temporal complexity of seismic data. In this paper, we analyze the complexity of seismic data and find that, it not only exists Gutenberg-Richter law such as the relationship between the earthquake frequency and earthquake magnitude, but also shows allometric growth laws for the relation between the average maximum magnitude of a region and its earthquake frequency.
For further studying the complexity of seismic data and the formation of earthquakes, we have presented an evolution model of earthquake networks based on complex networks theory with introducing geological data. This method constructs the relationships between earthquakes based on the seismic dataset and the geographic data of rock masses. According to the dynamical analysis of earthquake networks over time, we find out some significant evolution properties of earthquake networks, which is helpful to reveal the interactions between rock masses. The modeling idea is different from previous studies, because the entire region is divided by rock masses rather than a rectangular grid. The seismic dataset deriving from the Sichuan seismic station and the rock mass dataset providing by SKLGP (State Key Laboratory of Geohazard Prevention and Geoenvironment Protection) are used for experiments. The results indicate that the earthquake network can be described by a power law that the exponent is different from previous studies. Our work contributes to the spatio-temporal complexity research of earthquake seismic dataset and presents a new modeling idea of earthquake networks from the geological structure perspective.