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.
Cite
CITATION STYLE
Potter, W. D., Bi, W., Twardus, D., Thistle, H., Twery, M. J., Ghent, J., & Teske, M. (2000). Aerial spray deposition management using the genetic algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1821, pp. 210–219). Springer Verlag. https://doi.org/10.1007/3-540-45049-1_26
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