This study proposes a Machine Learning (ML)-based classification framework for RI prediction that utilizes Support Vector Machines (SVM) in conjunction with the Synthetic Minority Oversampling Technique (SMOTE) to handle the class imbalance of RI and non-RI cases. The Statistical Hurricane Intensity Prediction Scheme (SHIPS) data for the years 1982 to 2017 for the Atlantic Ocean basin and 1990 to 2010 for the Indian Ocean basin, respectively, are used to train and evaluate the proposed framework. Independent testing is conducted on operational data from 2010 to 2020 for the Atlantic basin and reanalysis data from 2011 to 2017 for the Indian basin.
Flowchart for the RI prediction framework.