Dynamics of the Markov Time Scale of Seismic Activity May Provide a   Short-Term Alert for Earthquakes
  We propose a novel method for analyzing precursory seismic data before an earthquake that treats them as a Markov process and distinguishes the background noise from real fluctuations due to an earthquake. A short time (on the order of several hours) before an earthquake the Markov time scale $t_M$ increases sharply, hence providing an alarm for an impending earthquake. To distinguish a false alarm from a reliable one, we compute a second quantity, $T_1$, based on the concept of extended self-similarity of the data. $T_1$ also changes strongly before an earthquake occurs. An alarm is accepted if {\it both} $t_M$ and $T_1$ indicate it {\it simultaneously}. Calibrating the method with the data for one region provides a tool for predicting an impending earthquake within that region. Our analysis of the data for a large number of earthquakes indicate an essentially zero rate of failure for the method. 
M. Reza Rahimi Tabar, Muhammad Sahimi, K. Kaviani, M. Allamehzadeh, J.   Peinke, M. Mokhtari, M. Vesaghi, M.D. Niry, F. Ghas...