Application of real time recurrent neural network for seismic event detection
The paper presents the detection of earthquakes by the Real Time Recurrent Neural Network (RTRN). The model of the network, the method of teaching it, and the results of earthquakes detection recorded by seismic stations of the Institute of Geophysics, Polish Academy of Sciences, are described. In a typical Artificial Neural Network (ANN), output values depend on instantaneous input values only. The RTRN has recurrent connections between network elements. The network outputs also depend on preceding input values. Information about a whole seismogram may be then used to detect instantaneous features, such as spectrum, and, at the same time, to detect time changes of the signal, with no need of supplying the input with long windows or spectrograms. Therefore, this method is able to efficiently detect regional earthquakes and teleseismic events. The network was investigated for the artificially imposed noised data and the real data taken from the stations with a high level of noise. The RTRN is able to generalize the results of teaching during recognition of other earthquakes.
Bibliogr. 15 poz.