Title :
The Application of RBF Neural Network in Earthquake Prediction
Author :
Wang Ying ; Chen Yi ; Zhang Jinkui
Author_Institution :
Sch. of Comput. & Control, Guilin Univ. of Electron. Technol., Guilin, China
Abstract :
RBF (Radial Basis Function) neural network is used to predict the magnitude of earthquake in this article. The self-adaptive and nonlinear approach abilities of RBF neural network are suitable to process the complexity of the production mechanism of earthquake. Firstly, RBF neural network is used to learn the data which include the information of earthquake. Then, use the trained RBF neural network to predict the test samples. The reasonable results indicate that the method has certain application value.
Keywords :
earthquakes; geophysics computing; radial basis function networks; RBF neural network; earthquake magnitude; earthquake prediction; nonlinear approach; production mechanism; radial basis function neural network; self-adaptive approach; Application software; Computer applications; Computer networks; Earthquakes; Feedforward neural networks; Function approximation; Genetics; MATLAB; Neural networks; Neurons; RBF; application; earthquake; predict;
Conference_Titel :
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-0-7695-3899-0
DOI :
10.1109/WGEC.2009.81
