Abstract
AbstractA numerical avalanche-prediction scheme was developed for highway applications at Kootenay Pass, British Columbia. The model features parametric discriminant analysis using Bayesian statistics to predict avalanche occurrences. Cluster techniques are then employed in discriminant space to analyze avalanche occurrences by the method of nearest neighbours. Extensive numerical testing of the model using an historical data base indicates that prediction accuracy may be 70% or better for both avalanche and non-avalanche time intervals.
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