APPLICATION OF GSM-SVM IN EARTHQUAKE MAGNITUDE PREDICTION
In view of numerous and redundant factors affecting earthquake magnitude,in order to predict earthquake magnitude effectively,a seismic magnitude prediction model based on support vector machine(SVM)optimized by grid search method was proposed.Selecting 7 influencing fac-tors,including cumulative earthquake frequency,cumulative released energy,b-value,number of abnormal earthquake swarms,number of seismic bands,activity period,and magnitude of related areas.Principal component analysis(PCA)was used to remove redundant information between fac-tors,and the input dimensions was reduced,and grid search method(GSM)was used to determine SVM parameters C and g,finally the magnitude prediction model was established,which was used to predict test samples,and compared with the prediction results of Genetic Algorithm(GA)and Parti-cle Swarm Optimization(PSO).The results showed that the average relative error of PCA-GSM-SVM was 1.29％,which had higher prediction accuracy.
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