Abstract
Earthquake Prediction is one of the most difficult subjects in the world. It is difficult to simulate the non-linear relationship between the magnitude of earthquake and many complicated attributes arising the earthquake. In this paper, RBF neural network ensemble was employed to predict the magnitude of earthquake. Firstly, the earthquake examples were divided to several training sets based on Bagging algorithm. Then a component RBF neural network, which was optimized by Adaptive Genetic Algorithm, was trained from each of those training sets. The result was obtained by majority voting method, which combined the predictions of component neural networks. Experiments demonstrated that the prediction accuracy was increased through using RBF neural network ensemble.
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Liu, Y., Wang, Y., Li, Y., Zhang, B., Wu, G. (2004). Earthquake Prediction by RBF Neural Network Ensemble. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_153
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DOI: https://doi.org/10.1007/978-3-540-28648-6_153
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