Analysing the causes of cyclonic severity in bay of bengal and its effects in biotic species using XGBoost algorithm

The severity of the cyclone depends on the amount of the pressure drop in the centre and the rate at which it increases outwards. The importance for the prediction of cyclone intensity ⁷ is growing day by day. In this paper we are addressing about the four type of severity of cyclone-Depression(D), Deep Depression(DD), Cyclonic Storm(CS), Super Cyclonic Storm (SCS). The objective of the work is predicting the cyclone severity using the wind speed, latitude, longitude of the pressure. When the severity is predicted well in advance then it will be very useful for the disaster management for proper planning. In this paper we are applying Xgboost model of linear regression for prediction. Xgboost is a gradient boosting algorithm which is based on decision tree. The model is trained with the dataset of 10 years (1990–2000) containing latitude, longitude and pressure drop of the cyclones occurred in Bay of Bengal (BOB) along with the date and time. Added to this, Cyclone or hurricane causes many hindrance to the Biotic Species including Land and Sea animals, plants, etc,.