Abstract:
Accurate forecast of cyclone intensities is important for disaster preparedness
in the coastal areas. Intensity prediction becomes especially difficult when they
undergo rapid intensification (RI). The inability to predict RI comes from the
fact that the physical processes that contribute to the cyclonic intensification are
not very well understood. Data mining techniques are being used to find the
relationship between change in the environmental variable values, and intensification.
Though good at identifying precursors to rapid intensification, data
mining techniques are computationally expensive. Moreover, very few studies
are conducted for the Bay of Bengal region, despite it being a hotbed of cyclonic
systems. In our work, we used a computationally cheaper LSH-SNN algorithm
to identify precursors to rapid intensification in Bay of Bengal, and showed its
effectiveness in identifying precursors.
