Application of Artificial Intelligence to Operational Real-Time Clear-Air Turbulence Prediction

Jennifer Abernethy, Robert Sharman, Elizabeth Bradley

Turbulence prediction is an important challenge to the aviation community because accurate forecasts are critical for the safety of the millions of people who fly every year. This paper details work in applying two AI techniques, support vector machines and logistic regression, to clear-air turbulence prediction. We show not only improved forecast accuracy over the current product performance, but also complete feasibility as part of a real-time operational turbulence forecasting system.

Subjects: 1.6 Engineering And Science; 16. Real-Time Systems

Submitted: Mar 27, 2008


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