CHARACTERISTIC OF AUTOREGRESSIVE MOVING AVERAGE AND ITS APPLICATION TO THE MODELING OF SEISMOLOGY IN BANDARABBAS ZONE, SOUTHERN PART OF IRAN  Fulltext 

[ Kavei ] - Department of Physics, Hormozgan University, Bandarabbas, Iran and Department of Environmental Sciences, Pune University, Pune, India
[ Gore ] - Department of statistics, Pune University, Pune, India
[ Ghassem Alaskari ] - Petroleum University of Technology, Ahwaz, Iran
[ Pawar ] - Department of geology, Pune University, Pune, India

خلاصه مقاله:

Over 180 earthquakes that occurred in Bandarabbas zone (Hormozgan province), southern part of Iran (27º - 28º N, 56º - 57º E) recorded between 1930 and 2006 have been analyzed. These events belong to many active faults and seismically active tectonic region in this analyized area. This complex situation has resulted in a series of earthquakes which have had more severe and damaging impact on the life and properties. These earthquakes of magnitude 5 and above (Mb = 5) have disrupted the socio-economic conditions, thousands have been rendered homeless and hundreds have been killed. The generation of synthetic event samples that can reproduce the essential statistical features of historical earthquakes is useful for the planning, design, and operation of site selections. Catalogues of earthquakes are continuously used based on statistical methods that they occurred in time. In the present study we used the Auto Regressive Moving Average (ARMA) of Bandarabbas zone and the result indicated that model identification and simulation techniques used to capture the variations in catalogues statistics are useful. The innovations algorithm is used to obtain parameter estimates. An application to annual data for zone of Bandarabbas city in southern part of Iran is included. A careful statistical analysis of the ARMA residuals produces a realistic simulation of this zone. In addition one more characteristic, distance the nearest fault from each epicenter, was analyzed.

Catalogue, Tectonic, Fault, Magnitude, Body waves, ARMA model, Residuals.