Abstract
We summarize the distribution range of large-scale fires in Victoria over the years, and predict and explain that this model has good adaptability to the changes of fires. This paper proposes a model that predicts the cost of drones, based on screening all possible ignition points. In order to ensure economy and security, we use cluster analysis to divide the selected ignition points into 9 categories, introduce 0-1 variables, use model annealing algorithm to find the shortest path, iterative search, and obtain the global optimal solution of the optimization problem. We need to send a total SSA 162 UAVs, and SSA UAV equipment increased by 141, equipment costs increased by $1410000.
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