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Parallel Dynamic Data Driven Genetic Algorithm for Forest Fire Prediction

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Recent Advances in Parallel Virtual Machine and Message Passing Interface (EuroPVM/MPI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5759))

Forest Fire Spread Prediction

Forest fire simulators are a very useful tool for predicting fire behavior. A forest fire simulator needs to be fed with data related to the environment where fire occurs: terrain main features, weather conditions, fuel type, fuel load and fuel moistures, wind conditions, etc. However, it is very difficult to obtain the real values of these parameters during a disaster [1]. The lack of accuracy of the input parameter values adds uncertainty to any prediction method and it usually provokes low quality simulations.

This work has been supported by the MEC-Spain under contracts TIN 2007-64974.

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References

  1. Bianchini, G.: Wildland Fire Prediction based on Statistical Analysis of Multiple Solutions. Ph. D Thesis. Universitat Autònoma de Barcelona (Spain) (July 2006)

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  2. Denham, M., Cortés, A., Margalef, T.: Computational Steering Strategy to Calibrate Input Variables in a Dynamic Data Driven Genetic Algorithm for Forest Fire Spread Prediction. In: Allen, G., et al. (eds.) ICCS 2009, Part II. LNCS, vol. 5545, pp. 479–488. Springer, Heidelberg (2009)

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  3. Foster, I.: Designing and Building Parallel Programs (Online). In: Message Passing Interface, ch. 8. Addison-Wesley, Reading (1995), http://www-unix.mcs.anl.gov/dbpp/text/node94.html

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  4. MPE_Open_Graphics, http://www-unix.mcs.anl.gov (Accessed on September 2008)

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© 2009 Springer-Verlag Berlin Heidelberg

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Denham, M., Cortés, A., Margalef, T. (2009). Parallel Dynamic Data Driven Genetic Algorithm for Forest Fire Prediction. In: Ropo, M., Westerholm, J., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2009. Lecture Notes in Computer Science, vol 5759. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03770-2_40

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  • DOI: https://doi.org/10.1007/978-3-642-03770-2_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03769-6

  • Online ISBN: 978-3-642-03770-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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