High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning

HIGHLIGHTS

• who: Atmos. Meas. Tech. et al. from the Wind Energy Computational Sciences, Sandia National Laboratories, Albuquerque, NM, USAThe approach leverages data from a field experiment involving a continuous-wave (CW) SpinnerLidar from the Technical University of Denmark (DTU) that provided scans of have published the article: High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning, in the Journal: (JOURNAL) of 11/07/2017
• what: The work compares three such techniques including conventional thresholding advanced filtering and a novel application of supervised machine learning with ensemble neural networks . . .
  

   

  

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