Predicting the future behavior of tropical cyclones is a problem of great importance for the atmospheric science community with concrete applications. Researchers understand enough about modeling storm systems to predict their track, but forecasting their future intensity remains elusive. In my MSc thesis, I formulated the tropical storm intensification prediction problem as a regression task and tried different techniques at all levels (preprocessing, model formulation and post-processing), examining the results and discussing their impact. My starting point was the Statistical Hurricane Intensity Prediction Scheme (SHIPS). The overall objectives were the derivation of better predicting models and the discovery of interesting patterns in the dataset at hand. With a colleague of mine in CSU, Andrew Sutton, we have approached the problem as a classification task, predicting whether the storm will intensify, abate or maintain its speed using particle swarm optimization and class association rules.
Master Thesis, Department of Computer Science, Colorado State University