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Aerial Spray Deposition Management Using the Genetic Algorithm

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Intelligent Problem Solving. Methodologies and Approaches (IEA/AIE 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,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.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Center, University of Georgia, USA

    W. D. Potter & W. Bi

  2. United States Department of Agriculture, Forest Service, USA

    D. Twardus, H. Thistle, M. J. Twery & J. Ghent

  3. Continuum Dynamics, Princeton, NJ

    M. Teske

Authors
  1. W. D. Potter
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  2. W. Bi
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  3. D. Twardus
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  4. H. Thistle
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  5. M. J. Twery
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  6. J. Ghent
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  7. M. Teske
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Editor information

Editors and Affiliations

  1. The Center for Advanced Computer Studies, University of Lousiana, 2 Rex Street, Lafayette, LA, 70504-4330, USA

    Rasiah Logananthara

  2. Department of Neural Information Processing, University of Ulm, Oberer Eselsberg, 89069, Ulm, Germany

    Günther Palm

  3. Department of Computer Science, Southwest Texas State University, 601 University Drive, San Marcos, TX, 78666-4616, USA

    Moonis Ali

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© 2000 Springer-Verlag Berlin Heidelberg

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Potter, W.D. et al. (2000). Aerial Spray Deposition Management Using the Genetic Algorithm. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_26

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  • DOI: https://doi.org/10.1007/3-540-45049-1_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67689-8

  • Online ISBN: 978-3-540-45049-8

  • eBook Packages: Springer Book Archive

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