1 research outputs found
Predicting Future Mosquito Habitats Using Time Series Climate Forecasting and Deep Learning
Mosquito habitat ranges are projected to expand due to climate change. This
investigation aims to identify future mosquito habitats by analyzing preferred
ecological conditions of mosquito larvae. After assembling a data set with
atmospheric records and larvae observations, a neural network is trained to
predict larvae counts from ecological inputs. Time series forecasting is
conducted on these variables and climate projections are passed into the
initial deep learning model to generate location-specific larvae abundance
predictions. The results support the notion of regional ecosystem-driven
changes in mosquito spread, with high-elevation regions in particular
experiencing an increase in susceptibility to mosquito infestation