Detailed comparison of the skills of NN and LR algorithms in predicting severe weathers on dependent and independent datasets showed that NN approach, with its nonlinear and collective expression of all the candidate predictors, provided higher forecast scores when comparing to the forward-selection method based on linear expression of a few selected predictors. Thus NN is more capable of detecting characteristic patterns of severe weather events that may exist in the statistical datasets.
The algorithms were developed to serve as the Severe Weather Threat Index (i.e. probability to produce severe weather) in the Systems for Convective Analysis and Nowcasting (SCAN), a suite of Advanced Weather Interactive Processing System (AWIPS), to automatically generate probabilities that individual thunderstorms will produce severe weather such as tornado, large hail and damaging wind.
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