Detection of atmospheric thermal flows by use of artificial neural network

This article analyses the determination of a rising thermal flow with assistance of an artificial neural network. Input data for the artificial neural network are derived from aircraft navigation equipment. The output data of the artificial neural network is the assessment of rising or descending airflow conducted in real time. Simulation is carried out in idealized conditions. The simulation revealed the dependence of absolute error on the vertical air speed component and the aircraft's aerodynamic parameters.

• Record URL:
  https://doi.org/10.3846/16487788.2011.626227
• Record URL:
  http://www.tandfonline.com/doi/abs/10.3846/16487788.2011.626227
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/16487788
• Supplemental Notes:
  • Abstract reprinted with permission from Taylor and Francis
• Authors:
  • Stankunas, Jonas
  • Suzdalev, Ivan
• Publication Date: 2011-9

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: pp 57-62
• Serial:
  • Aviation
  • Volume: 15
  • Issue Number: 3
  • Publisher: Vilnius Gediminas Technical University (VGTU) Press
  • ISSN: 1648-7788
  • EISSN: 1822-4180
  • Serial URL: https://journals.vgtu.lt/index.php/Aviation/about
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Aerodynamics; Airspeed; Flight dynamics; Navigation systems; Neural networks; Simulation
• Subject Areas: Aviation; Vehicles and Equipment;

Filing Info

• Accession Number: 01355891
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 19 2011 11:52AM