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
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;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.781