Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9521563 | Cold Regions Science and Technology | 2005 | 13 Pages |
Abstract
Two 10 fold cross validated classification trees were created, and suggested for use in forecasting. The classification tree with highest accuracy of 85% predicted avalanche days less well at 79%. An alternative tree using only wind speed and wind speed and precipitation combined in a temperature sensitive wind drift parameter resulted in a lower overall accuracy of 78%, but permitted a higher rate of correct prediction for avalanche days at 86%. The alternative, more conservative tree also reduced the number of false negative cases (observed as avalanche days, but predicted as non-avalanche days) from 31 to 20 at a cost of increasing the false positive or false alarm rate.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Earth and Planetary Sciences (General)
Authors
Jordy Hendrikx, Ian Owens, Wayne Carran, Ann Carran,