This paper introduces the method of support vector machine （SVM） into the field of synthetic earthquake prediction, which is a non-linear and complex seismogenic system. As an example, we apply this method to predic...This paper introduces the method of support vector machine （SVM） into the field of synthetic earthquake prediction, which is a non-linear and complex seismogenic system. As an example, we apply this method to predict the largest annual magnitude for the North China area （30°E-42°E, 108°N-125°N） and the capital region （38°E-41.5°E, 114°N-120°N） on the basis of seismicity parameters and observed precursory data. The corresponding prediction rates for the North China area and the capital region are 64.1% and 75%, respectively, which shows that the method is feasible.展开更多
基金supported by the Key Project of Science and Technology Supporting Plan of Tianjin Scientific Commission (No. 07ZCGYSF03100)
文摘This paper introduces the method of support vector machine （SVM） into the field of synthetic earthquake prediction, which is a non-linear and complex seismogenic system. As an example, we apply this method to predict the largest annual magnitude for the North China area （30°E-42°E, 108°N-125°N） and the capital region （38°E-41.5°E, 114°N-120°N） on the basis of seismicity parameters and observed precursory data. The corresponding prediction rates for the North China area and the capital region are 64.1% and 75%, respectively, which shows that the method is feasible.
