K09 : Comparison of regression algorithms for multivariable drought analysis


Students Maria Chzhen
School HWDSB - Westdale Secondary School - Hamilton
Level Senior 11/12 - Grade 12
Group Group 8 - Engineering and Computing II
Abstract The purpose of my project is to compare the performance of machine learning algorithms for analyzing droughts in various areas around the world and quantifying the correlation between drought and various factors, including wind speeds, evapotranspiration, precipitation, soil moisture, minimum and maximum temperature, vapour pressure, and CO2 emissions. The project also aims to identify region-based measures that humans can take to decrease the likelihood and impact of droughts.
Awards
Group Award Prize
Mohawk College Mathematics AwardsMohawk College Mathematics Awards - Senior$ 50
Merit AwardsSilver Merit Award$ 80
Canada-Wide Science Fair Trip AwardsCanada-Wide Science Fair Trip Award
McMaster University School of Earth Environment and SocietyEarth and Environmental Sciences Award$ 100
Mohawk College Computer Science & Information Technology Excellence AwardsMohawk College Computer Science & Information Technology Excellence Award$ 50
Canadian Meteorological and Oceanographic Society AwardsCanadian Meteorological and Oceanographic Society (CMOS) Award - Second$ 50
one year Free membership to CMOS