An adaptive system for forest fire behavior prediction

Roque Rodriguez*, Ana Cortés, Tomás Margalef, Emilio Luque

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

13 Citas (Scopus)

Resumen

In this paper, we propose a combination of two Dynamic Data Driven Application System (DDDAS) methodologies to predict wildfires' propagation. Our goal is to build a system that dynamically adapts to constant changes in environmental conditions when a hazard occurs and under strict real-time deadlines. For this purpose, we are on the way of building a parallel wildfire prediction method, which is able to assimilate real-time data to be injected in the prediction process at execution time.

Idioma originalInglés
Páginas (desde-hasta)275-282
Número de páginas8
PublicaciónProceedings - 2008 IEEE 11th International Conference on Computational Science and Engineering, CSE 2008
DOI
EstadoPublicada - 2008

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