Volume 12 Issue 1 (March-May 1996)

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Probability Judgmental Forecasting
edited by G. Wright, M.J. Lawrence, F. Collopy

Hailfinder: A Bayesian system for forecasting severe weather

Abramson, B. , Brown, J. , Edwards, W. , Murphy, A. , Winkler, R.L.
Pages 57-71
Abstract

Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.

Keywords: Bayesian , Belief networks , Meteorology , System design , Weather forecasting , Intelligent systems , Elicitation
FULL TEXT LINK
http://dx.doi.org/10.1016/0169-2070(95)00664-8
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