Prediction of peak ground motion for on-site earthquake early warning based on SVM

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Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (3) : 63-72.

YU Cong1,2, SONG Jindong1,2, LI Shanyou1,2

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Abstract

Here, taking ground motion peak values PGA and PGV synthesized by 3-D vectors after 0.1-10 Hz band-pass filtering as the prediction target parameters, using the data of 3 seconds after triggering P wave of Japan K-net strong earthquake network, based on the classic machine learning method in artificial intelligence-support vector machine (SVM), a ground motion peak value prediction model was constructed by selecting 8 feature parameters including acceleration amplitude Pa, velocity amplitude Pv, displacement amplitude Pd, Fourier spectrum amplitude AMmax, velocity square integral IV2, destruction intensity DI, cumulative absolute velocity CAV and Arias intensity Ia. Results showed that compared with the conventional Pd prediction model, using the constructed SVM prediction model for PGA and PGV, the predicted values calculated with testing data set and data sets of 2 earthquake cases selected randomly and the actual measured values are closer to a 1∶1 relationship, the errors for the predicted values of PGA and PGV are not affected by the change in epicenter distance; phenomena of under-estimation and over-estimation of PGA and PGV during prediction are improved; the constructed SVM prediction model can be used to predict ground motion peak values for in situ earthquake warning, i.e., to predict the instrument seismic intensity.

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earthquake early warning / on-site / P wave / ground motion peak value / support vector machine (SVM)

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YU Cong1,2, SONG Jindong1,2, LI Shanyou1,2. Prediction of peak ground motion for on-site earthquake early warning based on SVM[J]. Journal of Vibration and Shock, 2021, 40(3): 63-72

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