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Hurricane_ML_proj_t5

Term: Spring 2025

  • Team 5

  • Team members

    • Alessandro Castillo
    • Kechao Lu
    • Primanta Bangun
    • Sarah Pariser
  • Project summary: In this project, we aim to clarify the driving forces of hurricane impacts, not only taking storm intensity and frequency into consideration but also incorporating a wider range of perspectives such as affetced population and GDP. By merging the storm track dataset with storm destruction dataset (since 1980), we obtained 50 destrictive storms that have documented CPI_adjusted costs and deaths. We first analyzed the effectiveness of clustering by track shape in identifying destrictive storms, and then built regression models incorporating several relevant variables (intensity, population, gdp, duration, storm size and storm location) to identify the most significant factors that drives hurricane impacts.

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