TY - GEN
T1 - Application of artificial intelligence to operational real-time clear-air turbulence prediction
AU - Abernethy, Jennifer
AU - Sharman, Robert
AU - Bradley, Elizabeth
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/57749119275
M3 - Conference contribution
AN - SCOPUS:57749119275
SN - 9781577353683
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1649
EP - 1654
BT - AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
T2 - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
Y2 - 13 July 2008 through 17 July 2008
ER -