Short Term Earthquake Prediction in Hindukush Region Using Tree Based Ensemble Learning

Earthquake prediction has been long considered as impossible phenomenon but recent research studies show some progress in this field by considering it as a data mining problem. There are numerous challenges in earthquake prediction, which includes highly non-linear behavior of seismic activity and non-availability of reliable seismic precursors. This work focuses on earthquake prediction in Hindukush region by employing mathematically computed seismic features and using these features to model earthquake occurrences through employing machine learning techniques. The study aims to consider earthquake prediction as a binary classification problem. The short term earthquake prediction is performed using tree based ensemble classifiers, where rotation forest has shown good prediction results, compared to random forest and rotboost.