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Aerial Spray Deposition Management Using the Genetic Algorithm

  • W. D. Potter
  • W. Bi
  • D. Twardus
  • H. Thistle
  • M. J. Twery
  • J. Ghent
  • M. Teske
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1821)

Abstract

The AGDISP Aerial Spray Simulation Model is used to predict the deposition of spray material released from an aircraft. The prediction is based on a well-defined set of input parameter values (e.g., release height, and droplet size) as well as constant data (e.g., aircraft and nozzle type). But, for a given deposition, what are the optimal parameter values? We use the popular Genetic Algorithm to heuristically search for an optimal or near-optimal set of input parameters needed to achieve a certain aerial spray deposition.

Keywords

Genetic Algorithm Droplet Size Spray Parameter Maximum Fitness Swath Width 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • W. D. Potter
    • 1
  • W. Bi
    • 1
  • D. Twardus
    • 2
  • H. Thistle
    • 2
  • M. J. Twery
    • 2
  • J. Ghent
    • 2
  • M. Teske
    • 3
  1. 1.Artificial Intelligence CenterUniversity of GeorgiaUSA
  2. 2.United States Department of AgricultureForest ServiceUSA
  3. 3.Continuum DynamicsPrinceton

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