Abstract:On the basis of the F2 layer peak electron density(NmF2) from University Corporation for Atmospheric Research(UCAR), we constructed a Back Propogation(BP) artificial neural network(ANN) in order to detect preearthquake anomalies for the first time. The ANN provides NmF2 model value with five parameters:DOY,local time(LT), longitude(LON), latitude(LAT) and solar activity index of F10.7(FLUX). We compare the model value with observations during the Wenchuan earthquake. It is found that NmF2 around the forthcoming epicenter decreased remarkably in the afternoon period of day 6-4 before the earthquake, but enhanced day 3-2 before the earthquake.
Xiong Jing,,Wu Yun. IONOSPHERIC ELECTRON DENSITY ANOMALIES DETECTED BY BP ARTIFICIAL NEURAL NETWORK BEFORE WENCHUAN EARTHQUAKE[J]. jgg, 2013, 33(1): 13-16.