Constructing of an Efficient Model for Tornado Prediction Based on the Data Obtained from the University of Oklahoma

Student: Demin Sergey

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2016

The problem of tornado prediction is studied. Nowadays to forecast these disasters occurrence dynamic models are mainly used. However, this approach is time and resource consuming. Thus, we propose to use methods of smart data analysis in order to fasten the model and increase its prediction accuracy. In our study currently used tornado prediction methods and main mechanisms of tornado genesis were analyzed. As a result of our study, a model, based on decision trees, has been built. For efficiency evaluation, constructed model has been tested on real-life data obtained from the University of Oklahoma (USA). It is shown that constructed tornado prediction model is more efficient than all previous models.

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