Using random forests to diagnose aviation turbulence

@inproceedings{Williams2013UsingRF,
  title={Using random forests to diagnose aviation turbulence},
  author={John K. Williams},
  booktitle={Machine Learning},
  year={2013}
}
Atmospheric turbulence poses a significant hazard to aviation, with severe encounters costing airlines millions of dollars per year in compensation, aircraft damage, and delays due to required post-event inspections and repairs. Moreover, attempts to avoid turbulent airspace cause flight delays and en route deviations that increase air traffic controller workload, disrupt schedules of air crews and passengers and use extra fuel. For these reasons, the Federal Aviation Administration and the… CONTINUE READING
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