Joint Session 69 Advances in the Use of Artificial Intelligence Techniques in Support of Aviation, Range, and Aerospace Meteorology

Thursday, 16 January 2020: 1:30 PM-3:00 PM
156BC (Boston Convention and Exhibition Center)

Cochairs:
Haig Iskendarian, MIT, Lincoln Laboratory, Lexington, MA and James M. Kurdzo, MIT Lincoln Laboratory, Lexington, MA

Description:

This session will feature AI applications for supporting aviation meteorology, including predicting turbulence, icing, and thunderstorms.


Papers:
1:30 PM
J69.1
Using a neural network to predict future radar frames
Claire Sheila Bartholomew, Met Office, Exeter, UK; University of Leeds, Leeds, United Kingdom; and D. Hogg, J. H. Marsham, and T. Howard

1:45 PM
J69.2
The WSR-88D Chaff Detection Algorithm Utilizing a Support Vector Machine based on Human Truthing
James M. Kurdzo, MIT Lincoln Laboratory, Lexington, MA; and B. J. Bennett, D. J. Smalley, M. F. Donovan, and E. R. Williams

2:00 PM
J69.3
Global Synthetic Weather Radar in AWS GovCloud for the US Air Force
Mark S. Veillette, MIT Lincoln Laboratory, Lexington, MA; and H. Iskenderian, P. M. Lamey, C. J. Mattioli, A. Banerjee, M. Worris, A. B. Proschitsky, R. F. Ferris, A. Manwelyan, S. Rajagopalan, H. Usmani, T. E. Coe, J. E. Luce, and B. A. Esgar

2:15 PM
J69.4
Detection of Aircraft Lightning Potential Areas by using a Deep Neural Network with Interpretability
Eiichi Yoshikawa, Japan Aerospace Exploration Agency, Mitaka, Japan; and T. Ushio

2:30 PM
J69.5
Improvements to Convective Weather Avoidance Modeling Using Supervised Learning
Christopher J. Mattioli, MIT Lincoln Laboratory, Lexington, MA; and M. Matthews, H. Iskendarian, and M. S. Veillette

2:45 PM
J69.6
Short-term Wind Forecasts for Aviation*
William J. Dupree, MIT Lincoln Laboratory, Lexington, MA; and M. S. Veillette, A. Banerjee, J. P. Morgan, T. Bonin, H. Iskenderian, and M. McPartland

Abstract Submissions Closed



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