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

See all articles by Fuad T. Aleskerov

Fuad T. Aleskerov

National Research University Higher School of Economics

Nikita Baiborodov

Moscow Institute of Physics and Technology

Sergey Demin

National Research University Higher School of Economics

Sergey Shvydun

National Research University Higher School of Economics; Trapeznikov Institute of Control Sciences RAS

Theodore Trafalis

University of Oklahoma

Michael Richman

University of Oklahoma

Vyacheslav Yakuba

National Research University Higher School of Economics

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

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

Fuad T. Aleskerov

National Research University Higher School of Economics ( email )

20 Myasnitskaya Ulitsa
Moscow, 101000
Russia

Nikita Baiborodov

Moscow Institute of Physics and Technology ( email )

Institusky lane, 9
Dolgoprudny, Moskovskaya oblast
Russia

Sergey Demin

National Research University Higher School of Economics ( email )

Sergey Shvydun (Contact Author)

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

Trapeznikov Institute of Control Sciences RAS ( email )

65 Profsoyuznaya street
Moscow, 117997
Russia

Theodore Trafalis

University of Oklahoma ( email )

307 W Brooks
Norman, OK 73019
United States

Michael Richman

University of Oklahoma ( email )

307 W Brooks
Norman, OK 73019
United States

Vyacheslav Yakuba

National Research University Higher School of Economics

136, Rodionova street
25/12, Bolshaya pecherskaya street
Nizhniy Novgorod, 603155
Russia

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