Automatic Evolutionary Adjustment of Cellular Automata Model for Forest Fire Propagation
Authors: 
Maria Eugênia A. Ferreira, André L. M. P. Quinta, Danielli A. Lima, Luiz G. A. Martins, Gina M. B. OliveiraAuthors Info & Claims
Pages 235 - 245
Abstract
Forest fires have faced a huge increase due to climate change threatening different biomes. Fire propagation modeling is a critical issue to prevent and control the damage of this phenomenon. Cellular automata shown to be efficient in the construction of such models. However, tuning the various parameters involved in these models is a difficult task. This work proposes a method of parameters adjustment of fire propagation models based on genetic algorithms. Different experiments in various scenarios showed that was possible to use evolutionary computation that automatically adjusts the parameters of a fire spread model.
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Information
Published In
Sep 2022
372 pages
ISBN:978-3-031-14925-2
DOI:10.1007/978-3-031-14926-9
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 12 September 2022
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