International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Constructing Efficient Regional Hazardous Weather Prediction Models through Big Data Analysis

  • Lee, Jaedong (Department of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Lee, Jee-Hyong (Department of Electrical and Computer Engineering, Sungkyunkwan University)
  • Received : 2016.02.27
  • Accepted : 2016.03.24
  • Published : 2016.03.25
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Abstract

In this paper, we propose an approach that efficiently builds regional hazardous weather prediction models based on past weather data. Doing so requires finding the proper weather attributes that strongly affect hazardous weather for each region, and that requires a large number of experiments to build and test models with different attribute combinations for each kind of hazardous weather in each region. Using our proposed method, we reduce the number of experiments needed to find the correct weather attributes. Compared to the traditional method, our method decreases the number of experiments by about 45%, and the average prediction accuracy for all hazardous weather conditions and regions is 79.61%, which can help forecasters predict hazardous weather. The Korea Meteorological Administration currently uses the prediction models given in this paper.

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References

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