METHODS FOR DIFFERENTIATION OF EARTHQUAKE SIGNAL AND PREDICTION OF EARTHQUAKE INTENSITY USING RANDOMLY GENERATED ARTIFICIAL SEISMIC TRAINING DATA FOR AN ARBITRARY ZONE

摘要

The present invention relates to an earthquake determination method using randomly generated seismic learning data for arbitrary seismic zones. The earthquake determination method, an earthquake determination method using an artificial neural network technique, performed by an earthquake intensity prediction system for predicting an earthquake intensity using seismic waves in a target zone, comprises the steps of: collecting past earthquake data of the target zone and deriving seismic wave characteristic data from the collected past earthquake data; performing a pseudo earthquake probability model which reflects the derived seismic wave characteristic data to randomly generate learning data on general vibration and seismic vibration for the target zone; providing the learning data generated through the pseudo earthquake probability model to artificial neural network learning; inputting, if an actual P wave is detected, the P wave to an artificial neural network to determine whether an earthquake occurs; and generating an artificial S wave to estimate a structure′s response through the artificial neural network technique and predicting a damage scale of the structure using the generated artificial S wave to provide an earthquake warning. Therefore, the earthquake determination method of the present invention can be applied to smart seismometers in a house, a building, or the like, to improve the accuracy and reliability of earthquake warnings. The earthquake determination method can be also employed in a structural health monitoring (SHM) technology in construction and civil engineering fields to analyze a seismic impact on a structure. Moreover, the earthquake determination method is applied to a construction site to enable quick early evacuation and facility control in case of a natural disaster on the construction site.