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)
Hosts: (Joint between the 19th Conference on Artificial Intelligence for Environmental Science; the 20th Conference on Aviation, Range, and Aerospace Meteorology; and the Events )
Cochairs:
Haig Iskendarian, MIT, Lincoln Laboratory, Lexington, MA and James M. Kurdzo, MIT Lincoln Laboratory, Lexington, MA

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; Univ. 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 U.S. 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
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner