An Intelligent Earthquake Early Waring Model Using JRG Sub-cluster Statistics Theory

Author

Li, Xuefei ; Fu, Peihong

Author_Institution

Sch. of Comput., Wuhan Univ., Wuhan, China

Volume

1

fYear

2011

fDate

28-29 March 2011

Firstpage

1010

Lastpage

1013

Abstract

Using strain precursor to predict the earthquake has proven to be crucial for earthquake early warning. However, there is currently problem that it is hard to establish more effective intelligent analyzing models for earthquake early warning. In this paper, we introduced the core concept and ideas of JRG Sub-cluster statistics theory and three risk limits at first. Meanwhile, we put forward the analyzing models for earthquake early warning system using JRG Sub-cluster theory. Then, the architecture of earthquake early warning system integrating early warning model, RS and GIS was put forward. Finally, Earthquake Early Warning System based on this architecture was implemented.

Keywords

earthquakes; geographic information systems; geophysical techniques; remote sensing; statistical analysis; GIS; JRG subcluster statistical theory; earthquake early warning system architecture; intelligent analyzing model; intelligent earthquake early waring model; remote sensing; Alarm systems; Analytical models; Computational modeling; Data models; Earthquakes; Monitoring; Strain; Earthquake early warning; Earthquake precursor; GIS; JRG Sub-cluster;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on

Conference_Location

Shenzhen, Guangdong

Print_ISBN

978-1-61284-289-9

Type

conf

DOI

10.1109/ICICTA.2011.253

Filename

5750770