Constructing an Efficient Machine Learning Model for Tornado Prediction
Higher School of Economics - National Research University, Working Paper WP7/2016/05, Series WP7
24 Pages Posted: 10 Jul 2018
Date Written: 2016
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.
Keywords: tornado prediction, superposition principle, data analysis
JEL Classification: D83, Q54
Suggested Citation: Suggested Citation
Aleskerov, Fuad T. and Baiborodov, Nikita and Demin, Sergey and Shvydun, Sergey and Trafalis, Theodore and Richman, Michael and Yakuba, Vyacheslav, Constructing an Efficient Machine Learning Model for Tornado Prediction (2016). Higher School of Economics - National Research University, Working Paper WP7/2016/05, Series WP7 , Available at SSRN: https://ssrn.com/abstract=3196968 or http://dx.doi.org/10.2139/ssrn.3196968
Do you have negative results from your research you’d like to share?
Feedback
Feedback to SSRN
If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday.