Estimation of the Future Earthquake Situation by Using Neural Networks Ensemble

Earthquakes will do great harms to the people, to estimate the future earthquake situation in Chinese mainland is still an open issue. There have been previous attempts to solve this problem by using artificial neural networks. In this paper, a novel algorithm named MIFEB is proposed to improve the estimation accuracy by combing bagging of neural networks with mutual information based feature selection for its individuals. MIFEB is compared with the general case of bagging on UCI data sets, then, MIFEB is used to forecast the seismicity of strong earthquakes in Chinese mainland, computation results show that MIFEB obtains higher accuracy than other several methods like bagging of neural networks and single neural networks do.