A repeated M8 algorithm and its application to the large Iranian earthquakes

Earthquake is a non-linear phenomenon, which occur in a very unpredictable way. Despite this fact earthquake is not a random process and has systematic orders, which is reflected on the fractal behavior of its temporal, magnitude and space distribution. The M8 algorithm is a pattern recognition algorithm for intermediate-term earthquake prediction ( a few weeks to a few years). Which exploits the hidden orders of seismicity flow to predict the time, location and magnitude of a future earthquake . In this work, we will show that the M8 algorithm has a significant intrinsic space uncertainty. We introduce a simple new method, the Repeated M8 or RM8 to reduce this space uncertainty. In this method the M8 algorithm is applied to a dense grid of circle of investigation and by finding the area shared by the issued TIPs a Highly probable Time of Increased probability (htip0 is calculated. We show that the method significantly ( up to about 20 times) reduces the space uncertainty of the M8 method . The method is applied to the retrospective prediction of 12 large worldwide earthquakes (M0=7.5 and 8=). Finally we report our forward prediction for the Iranian territory.

A repeated M8 algorithm and its application to the large Iranian earthquakes Keywords:

m8 prediction algorithm , Earthquake prediction , Iranian earthquakes