An Application of Adaptive Logic to Meteorological Prediction

Abstract

Two adaptive logic models and a training algorithm for each are described. These models are tested on a meteorological prediction problem with the use of large developmental and test data samples. Discriminant analysis is used for comparison. It is found that ceiling heights at Washington National Airport could be forecast better with the discriminant analysis technique than with the adaptive logic models.