Earthquake Magnitude Prediction Model Based on the GEP Algorithm and Markov Chain

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Abstract:

This paper introduces a method which uses the gene expression programming algorithm to conduct multivariate nonlinear function modeling, which is applied in the earthquake magnitude prediction. The experiment shows that the prediction accuracy of the GEP is significantly higher than that of the neural network model. Finally, by using the non-delayed effects and stability of the earthquake magnitude prediction data, the state-transition matrix is obtained through the Markov chain, and the state interval and corresponding probability of the GEP model prediction are obtained. In this way, the credibility of the prediction results has been increased.

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2130-2133

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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