특성 자료를 활용한 한반도 동남권 지역의 최대지반가속도 예측 연구
A Study on the Prediction of Peak Ground Acceleration in the Southeast Region of Korea Using Characteristic Data
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Early warnings have been developed to provide rapid earthquake information, allowing people to prepare as much time as possible. However, since it takes several seconds for an earthquake warning to be issued, the blind zone is inevitable. To reduce the blind zone, information from a single observatory is used to operate an on-site earthquake warning. However, false and missed alarms are still high, requiring continued research and validation. This study predicted Peak Ground Acceleration (PGA) using the characteristic data to reduce false and missed alarms in on-site earthquake warnings. A machine learning prediction model was created using the initial P-wave parameters developed from the characteristic data to achieve this. Then, the model was used to predict the maximum ground acceleration in the southeastern region of the Korean Peninsula. The expected results for six target earthquakes were confirmed to have a standard deviation within 0.3 compared to the observed PGA and the values within ±2 sigma. This method is expected to help develop an on-site early warning system for earthquakes.
Abstract
Early warnings have been developed to provide rapid earthquake information, allowing people to prepare as much time as possible. However, since it takes several seconds for an earthquake warning to be issued, the blind zone is inevitable. To reduce the blind zone, information from a single observatory is used to operate an on-site earthquake warning. However, false and missed alarms are still high, requiring continued research and validation. This study predicted Peak Ground Acceleration (PGA) using the characteristic data to reduce false and missed alarms in on-site earthquake warnings. A machine learning prediction model was created using the initial P-wave parameters developed from the characteristic data to achieve this. Then, the model was used to predict the maximum ground acceleration in the southeastern region of the Korean Peninsula. The expected results for six target earthquakes were confirmed to have a standard deviation within 0.3 compared to the observed PGA and the values within ±2 sigma. This method is expected to help develop an on-site early warning system for earthquakes.