The research is focused on the development of automatic detection method of abnormal features, that occur in recorded time series of ionosphere critical frequency fOF2 during periods of high solar or seismic activity....The research is focused on the development of automatic detection method of abnormal features, that occur in recorded time series of ionosphere critical frequency fOF2 during periods of high solar or seismic activity. The method is based on joint application of wavelet-transformation and neural networks. On the basis of wavelet transformation algorithms for the detection of features and estimation of their parameters were developed. Detection and analysis of characteristic components of time series are performed on the basis of joint application of wavelet transformation and neural networks. Method's approbation is performed on fOF2 data obtained at the observatory “Paratunka” (Paratunka settlement, Kamchatskiy Kray).展开更多
In the present work, disturbances of the half-transparency frequency fbEs of the ionospheric sporadic E-layer are investigated in connection with earthquakes. The fbEs-frequency is proportional to the square root of t...In the present work, disturbances of the half-transparency frequency fbEs of the ionospheric sporadic E-layer are investigated in connection with earthquakes. The fbEs-frequency is proportional to the square root of the maximum ionisation density of the sporadic E-layer. In this work, it is shown that in 2/3 of the cases, two days before a seismic shock with magnitude M > 5.5 and on the day of the shock, an increase of the fbEs-frequency is obtained at sunset hours at distances from the epicenter R km. In contrast, before sunrise, the fbEs-value decreases. The data analysed are obtained by the three vertical ionospheric sounding stations“Kokubunji”, “Yamagawa”, and “Wakkanai” during some tens of years.展开更多
文摘The research is focused on the development of automatic detection method of abnormal features, that occur in recorded time series of ionosphere critical frequency fOF2 during periods of high solar or seismic activity. The method is based on joint application of wavelet-transformation and neural networks. On the basis of wavelet transformation algorithms for the detection of features and estimation of their parameters were developed. Detection and analysis of characteristic components of time series are performed on the basis of joint application of wavelet transformation and neural networks. Method's approbation is performed on fOF2 data obtained at the observatory “Paratunka” (Paratunka settlement, Kamchatskiy Kray).
文摘In the present work, disturbances of the half-transparency frequency fbEs of the ionospheric sporadic E-layer are investigated in connection with earthquakes. The fbEs-frequency is proportional to the square root of the maximum ionisation density of the sporadic E-layer. In this work, it is shown that in 2/3 of the cases, two days before a seismic shock with magnitude M > 5.5 and on the day of the shock, an increase of the fbEs-frequency is obtained at sunset hours at distances from the epicenter R km. In contrast, before sunrise, the fbEs-value decreases. The data analysed are obtained by the three vertical ionospheric sounding stations“Kokubunji”, “Yamagawa”, and “Wakkanai” during some tens of years.
