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

fYear

2009

fDate

14-17 Oct. 2009

Firstpage

465

Lastpage

468

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on

Conference_Location

Guilin

Print_ISBN

978-0-7695-3899-0

Type

conf

DOI

10.1109/WGEC.2009.81

Filename

5402794

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3345294