Constructing an Efficient Machine Learning Model for Tornado Prediction

Fuad Aleskerov; Sergey Demin; Michael B. Richman; Sergey Shvydun; Theodore B. Trafalis; Vyacheslav Yakuba

doi:10.1142/S0219622020500261

Constructing an Efficient Machine Learning Model for Tornado Prediction

Fuad Aleskerov, Sergey Demin, Michael B. Richman, Sergey Shvydun, Theodore B. Trafalis, Vyacheslav Yakuba

Research output: Contribution to journal › Article › Scientific › peer-review

2 Citations (Scopus)

Abstract

Tornado prediction variables are analyzed using machine learning and decision analysis techniques. A model based on several choice procedures and the superposition principle is applied for different methods of data analysis. The constructed model has been tested on a database of tornadic events. It is shown that the tornado prediction model developed herein is more efficient than a previous set of machine learning models, opening the way to more accurate decisions.

Original language	English
Pages (from-to)	1177-1187
Number of pages	11
Journal	International Journal of Information Technology and Decision Making
Volume	19
Issue number	5
DOIs	https://doi.org/10.1142/S0219622020500261
Publication status	Published - 1 Aug 2020
Externally published	Yes

Keywords

data analysis
Machine learning
superposition principle
tornado prediction

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10.1142/S0219622020500261

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abstract = "Tornado prediction variables are analyzed using machine learning and decision analysis techniques. A model based on several choice procedures and the superposition principle is applied for different methods of data analysis. The constructed model has been tested on a database of tornadic events. It is shown that the tornado prediction model developed herein is more efficient than a previous set of machine learning models, opening the way to more accurate decisions.",

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AU - Richman, Michael B.

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AU - Trafalis, Theodore B.

AU - Yakuba, Vyacheslav

PY - 2020/8/1

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AB - Tornado prediction variables are analyzed using machine learning and decision analysis techniques. A model based on several choice procedures and the superposition principle is applied for different methods of data analysis. The constructed model has been tested on a database of tornadic events. It is shown that the tornado prediction model developed herein is more efficient than a previous set of machine learning models, opening the way to more accurate decisions.

KW - data analysis

KW - Machine learning

KW - superposition principle

KW - tornado prediction

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DO - 10.1142/S0219622020500261

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Constructing an Efficient Machine Learning Model for Tornado Prediction

Abstract

Keywords

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