Master of Science in Computer Science (MSCS)
wildfires, multi-criteria decision making, fuzzy set theory
Wildfires are uncontrolled fires that may lead to the destruction of biodiversity, soil fertility, and human resources. There is a need for timely detection and prediction of wildfires to minimize their disastrous effects. In this research, we propose a wildfire prediction model that relies on multi-criteria decision making (MCDM) to explicitly evaluates multiple conflicting criteria in decision making and weave the wildfire risks into the city’s resiliency plan. We incorporate fuzzy set theory to handle imprecision and uncertainties. In the process, we create a new data set that includes California cities’ weather, vegetation, topography, and population density records. The model ranks the cities of California based on their risk of wildfires.
Rani, Rekha, "Wildfire Risk Prediction for a Smart City" (2021). Master's Projects. 1014.