SEVERAL ORDER CLUSTERING METHODS FOR THE STUDY OF SEISMOGENIC PROCESS OF STRONG EARTHQUAKES

In this paper, the seismogenic process of strong earthquakes of North China and the Ningxia region is studied by using five order clustering methods. We found that all five methods can simulate the phenomena of alternatively high and low seimic activities; the better effects of both Fisher's method and order hierarchical clustering method (using incremental surn of squares of deviations as the between-class distance) show that the structures of time intervals in classes are mainly of cluster distribution and are not of chain distribution, thus it is important that this character of seismic activity should be considered in choosing the method of prediction. The results of Webster's method and nonpariametric goodness of fit show that there are centainly objective valle-yes between relatively queit periods and remarkably active periods. Then graph theory further helps us to distinguish the smialler peaks in which strong earthquakes are apt to occurr.The error of Fisher's method is smallest among these five methods, while noupara-metric goodness of fit can help make more reasonable classification. In addition, pre-srnoothing of data can also improve the results.