The role of the cell shapes on the characteristics of a complex earthquake network

We studied the behavior of earthquake network using HEALPix spherical pixelization and square cells methods. In first method, geographical region is divided into isolatitude rhombic-spherical same areas method. second we equal cells. To construct a network, if an happens in cell, that cell will become node, two nodes be connected with edge for successive events. The built from Iran’s seismic data 1900 June 12 to 2015 December 12. determined Hurst exponent (H = 0.6) due rescaled range (R/S) analysis. This value reveals long temporal correlation time-series; therefore, system suggested self-organized. showed among five major seismotectonic provinces Iran (Alborz-Azarbayejan, Kope Dagh, Central-East Iran, Zagros, Makran), hubs are located Zagros region, which seismically very active region. According this result, earthquakes affect surrounding earthquakes. probability distribution function’s power-law shows scale free behavior’s properties than constructed based on mean clustering coefficient’s nature networks methods scale-free non-random. concluded more reliable method building large region’s network.