Based on time series similarity matching algorithm for earthquake prediction research

On the basis of analyzing the newly time sequence research achievement nowadays, several definitions on seismological zone relativity are put forward in this paper for integrating the large amount of history earthquake source data and the experimental expert knowledge in seismological field. At the same time, the time sequence similarity-matching model of the relevant seismological zone is presented, and then it is implemented through several correlative experimental simulations. Based on the sequence similarity-matching model, a sequence-matching algorithm is given with seismological similarity. Furthermore, by discovering the history earthquake database in recent several years, some experiments are provided to analyze longitudinal thick-granularity sequential similarity and thin-granularity sequential similarity. Finally, the experimental result has found its satisfactory way out by using the proposed algorithm to support earthquake prediction.