關鍵字：地震震度預測、機器學習、隨機森林、地震P波擷取 ;Earthquakes are one of the major natural disasters on earth. When strong earthquakes occur, insufficient awareness of earthquakes and neglect of precautions often result in serious property losses and casualties. Taiwan is located in the Pacific Rim Seismic Belt, and seismic activity is Frequently, how to prevent earthquakes has become an important issue that cannot be ignored. This study attempts to build an earthquake early warning system. using seismic acceleration data in the Taoyuan (local) area obtained from the Central Meteorological Administration and publicly downloaded based on the theory of machine learning in artificial intelligence. The specific methods used in this thesis are random forest regression and classification models. These models capture the initial acceleration signals of the earthquake to predict the maximum ground acceleration (PGA) and magnitude of the current earthquake. This study also explores the influence of choosing different combinations of earthquake seismic wave (P wave) characteristics and adding virtual data for predicting the results.
