DocumentCode
3299448
Title
Magnitude of Earthquake Prediction Using Neural Network
Author
Suratgar, Amir Abolfazl ; Setoudeh, Farbod ; Salemi, Amir Hossein ; Negarestani, Ali
Author_Institution
Electr. Eng. Dept., Arak Univ., Arak
Volume
2
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
448
Lastpage
452
Abstract
This paper presents a new method for earthquake prediction. In the proposed method the variation of geomagnetic field declination, horizontal component and hourly relative humidity, temperature ground, rainy rate per day such as hum, rrr (the average of rainy hours time per day), and tgtg (temperature ground) are used to predict magnitude of earthquake 2 days before the occurrence of earthquake occurrence by using a neural network. As a case study, earth geomagnetic field measured data is used. The data are driven from the measurements collected in Tehran Geophysics Research Center in 1970 - 1976. Simulation results are very promising.
Keywords
atmospheric humidity; earthquakes; geomagnetism; geophysical techniques; geophysics computing; neural nets; rain; AD 1970 to 1976; Tehran Geophysics Research Center; earth geomagnetic field measured data; earthquake magnitude prediction; earthquake occurrence; geomagnetic field declination; neural network; rainy rate; relative humidity; temperature ground; Earth; Earthquakes; Electromagnetic radiation; Geomagnetism; Geophysical measurement techniques; Geophysical measurements; Ground penetrating radar; Land surface temperature; Neural networks; Seismic measurements; Earth; Magnetic; Neural network; Quake;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.781
Filename
4667035
Link To Document