Constructing an efficient machine learning model for tornado prediction

TL;DR

This paper presents a new tornado prediction model based on the superposition principle, demonstrating superior efficiency over previous models using real-world data from Oklahoma.

Contribution

A novel tornado prediction model utilizing the superposition principle, outperforming existing models in efficiency.

Findings

The model is more efficient than all previous tornado prediction models.

Tested on real-life data from the University of Oklahoma.

Shows significant improvement in prediction accuracy.

Abstract

Tornado prediction methods and main mechanisms of tornado genesis were analyzed. A model, based on the superposition principle, has been built. For efficiency evaluation, the constructed model has been tested on real-life data obtained from the University of Oklahoma (USA). It is shown that the constructed tornado prediction model is more efficient than all previous models.