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Simulation of Wildfire Spread Using Cellular Automata with Randomized Local Sources

机译:使用随机本地来源使用蜂窝自动机的野火涂抹

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The accuracy of Cellular Automata (CA) methods for simulating wildfires is limited by the fact that spread directions are constrained to the few angles imposed by the regular lattice of cells. To mitigate such problem, this paper proposes a new CA in which a local randomization of the spread directions is explicitly introduced over the lattice. The suggested technique, inspired by a method already used for simulating lava flows, is empirically investigated under homogeneous conditions and by comparison with the vector-based simulator FARSITE. According to the presented results, the adopted randomization seems to be able to significantly improve the accuracy of CA based on a standard center-to-center ignition scheme.
机译:用于模拟野火的蜂窝自动机(CA)方法的准确性受到扩散方向被限制为由常规细胞施加的几个角度限制的事实。为了减轻这样的问题,本文提出了一种新的CA,其中在格子上明确地引入了扩展方向的局部随机化。由已经用于模拟熔岩流的方法的建议的技术在均匀条件下经验研究,并与基于向量的模拟器的模拟器的比较进行了经验研究。根据所提出的结果,采用的随机化似乎能够基于标准中心到中心点火方案来显着提高CA的准确性。

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