Hybrid-Parallel Uncertainty Reduction Method Applied to Forest Fire Spread Prediction
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2017-04-01Autor
Méndez Garabetti, Miguel
Bianchini, Germán
Tardivo, María
Caymes Scutari, Paola
Gil Costa, Verónica
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Fire behavior prediction can be a fundamental tool to reduce losses and damages in mergency situations. However, this process is often complex and affected by the existence of ncertainty. For this reason, from different areas of science, several methods and systems are developed and refined to reduce the effects of uncertainty In this paper we present the Hybrid Evolutionary-Statistical System with Island Model (HESS-IM). It is a hybrid uncertainty reduction method applied to forest fire spread prediction that combines the advantages of two evolutionary population metaheuristics: Evolutionary Algorithms and Differential Evolution. We evaluate the HESS-IM with three controlled fires scenarios, and we obtained favorable results compared to the previous methods in the literature
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