Tornado detection with support vector machines

Abstract

Abstract. The National Weather Service (NWS) Mesocyclone Detec-tion Algorithms (MDA) use empirical rules to process velocity data from the Weather Surveillance Radar 1988 Doppler (WSR-88D). In this study Support Vector Machines (SVM) are applied to mesocyclone detection. Comparison with other classification methods like neural networks and radial basis function networks show that SVM are more effective in meso-cyclone/tornado detection.

Similar works

Full text

thumbnail-image

CiteSeerX

redirect
Last time updated on 29/10/2017

This paper was published in CiteSeerX.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.