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Complex Systems Modeling with Cellular Automata and Genetic Algorithms: An Application to Lava Flows

机译:用蜂窝自动机和遗传算法建模的复杂系统:熔岩流动的应用

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Cellular Automata are parallel computational models which are capable to give rise to heterogeneous emergent behaviors notwithstanding simple local rules of evolution. In this review paper, a methodology for modeling complex natural systems through Macroscopic Cellular Automata is presented and applied to lava flow simulation. In particular, the 2001 Mt. Etna volcano Nicolosi (Italy) case study has been considered for model calibration, while the validation has been performed by considering further cases of study, which differ both in duration and emission rate. Parameter optimization was carried out by a Parallel Master-Slave Genetic Algorithm. Results have confirmed both the goodness of the simulation model and of the calibration algorithm. Eventually an application related to Civil Defense purposes is briefly described and proposed as a development.
机译:蜂窝自动机是并行计算模型,尽管简单的局部演化规则,但是能够引起异构紧急行为。在该综述论文中,提出并应用于熔岩流动模拟的复杂天然系统的方法。特别是,2001年MT.Etna Volcano Nicolosi(意大利)案例研究已经考虑用于模型校准,而通过考虑进一步的研究案例,验证是在持续时间和排放率的情况下进行的验证。参数优化通过并行主从遗传算法执行。结果证实了仿真模型和校准算法的良善性。最终,简要描述并提出了与民防目的有关的申请作为发展。

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