Bootstrapping and Boosting Decision Tree based Ensemble Learning Algorithms Applied to the Iranian Strong Motion Data
Apr 2020 - Jan 2021 (10 months)
• Machine learning algorithms are applied on the Iranian earthquake for predicting the peak ground acceleration.
• The data set of different earthquakes are used to predict the earthquake response parameters
• Used four well-developed machine learning algorithms, i.e., decision tree, random forest, AdaBoost,and XGboost, to the seismic database and evaluate the best algorithm for the prediction.
• Submitted paper in the Iranian Journal of Earth Sciences and its under review.