Ground Motion Estimation Using Front Site Wave Form Data Based on RVM for Earthquake Early Warning
Yincheng Yang* and Masato Motosaka**
*Graduate School of Engineering, Tohoku University
Aramaki Aza-Aoba 468-1, Aoba-ku, Sendai 980-0845, Japan
**International Research Institute of Disaster Science, Tohoku University
Aramaki Aza-Aoba 468-1, Aoba-ku, Sendai 980-0845, Japan
The use of the earthquake early warning system (EEWS), one of the most useful emergency response tools, requires that the accuracy of real-time ground motion prediction (GMP) be enhanced. This requires that waveform information at observation points along earthquake wave propagation paths (hereafter, front-site waveform information) be used effectively. To enhance the combined reliability of different systems, such as on-site and local/regional warning, we present a GMP method using front-site waveform information by applying a relevant vector machine (RVM). We present methodology and application examples for a case study estimating peak ground acceleration (PGA) and peak ground velocity (PGV) for earthquakes in the Miyagi-Ken Oki subduction zone. With no knowledge of source information, front site waveforms have been used to predict ground motion at target sites. Five input variables – earthquake PGA, PGD, pulse rise time, average period and the Vpmax/Amax ratio – have been used for the first 4 to 6 seconds of P-waves in training a regression model. We found that RVM is a useful tool for the prediction of peak ground motion.
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