Abstract
One of the most serious problems in wildland fire simulators is the lack of precision for input parameters (moisture content, wind speed, wind direction, etc.). In this paper, a statistical method based on a factorial experiment is presented. This method evaluates a high number of parameter combinations instead of considering a single value for each parameter, in order to obtain a prediction which is closer to reality. The proposed methodology has been implemented in a parallel scheme and tested in a Linux cluster using MPI.
This work has been supported by the Comisión Interministerial de Ciencia y Tecnología (CICYT) under contract TIC2001-2592 and by the European Commission under contract EVG1-CT-2001-00043 SPREAD.
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Andrews, P.L.: BEHAVE: Fire Behavior prediction and modeling systems - Burn subsystem, part 1. General Technical Report INT-194. Odgen, UT, US Department of Agriculture, Forest Service, Intermountain Research Station (1986)
Andrews, P.L., Bevins, C.D., Seli, R.C.: BehavePlus fire modeling system, version 2.0: User’s Guide. Gen. Tech. Rep. RMRS-GTR-106WWW. Ogden, UT: Department of Agriculture, Forest Service, Rocky Mountain Research Station (2003)
Abdalhaq, B., Bianchini, G., Cortés, A., Margalef, T., Luque, E.: Improving Wildland Fire Prediction on MPI Clusters. In: Dongarra, J., Laforenza, D., Orlando, S. (eds.) EuroPVM/MPI 2003. LNCS, vol. 2840, pp. 520–528. Springer, Heidelberg (2003)
Bevins, C.D.: FireLib User Manual & Technical Reference (1996), http://www.fire.org
E-FIS A ten telecom project, http://www.e-fis.org/
Eftichidi, G., Varela, V.: SAFES: Safe Fire Expert System. Presentation in the International Scientific Conference Fires in the Mediterranean forests: Prevention -Suppression - Soil Erosion - Reforestation organised by UNESCO in Athens, 3-6 February (1999)
Finney, M.A.: FARSITE: Fire Area Simulator-model development and evaluation. Res. Pap. RMRS-RP-4, Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 47 p. (1998)
ADAI Products: FIRESTATION, http://www.adai.pt/products/firestation/
Rothermel, R.C.: A mathematical model for predecting fire spread in wildland fuels. USDA FS, Ogden TU, Res. Pap. INT-115 (1972)
ADAI - CEIF (Center of Forest Fire Studies), http://www.adai.pt/ceif/Gestosa/
MPI: The Message Passing Interface Standard, http://www-unix.mcs.anl.gov/mpi/
Prometheus. http://kentauros.rtd.algo.com.gr/promet/schedule.htm
Reinhardt, E.D., Keane, R.E., Brown, J.K.: First Order Fire Effects Model: FOFEM 4.0, User’s Guide. General Technical Report INT- GTR- 344 (1997)
Insua, S.R., Lozoya, C.B., Caballero, A.M.: Fundamento de los Sistemas de Ayuda a la decisión. RaMa 2002 (2002) ISBN 84-7897-494-6
Project Spread, Forest Fire Spread Prevention and Mitigation, http://www.adai.pt/spread/
Montgomery, D.C., Runger, G.C.: Probabilidad y Estadística aplicada a la Ingeniería. Limusa Wiley (2002) ISBN: 968-18-5914-6
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Bianchini, G., Cortés, A., Margalef, T., Luque, E. (2005). S 2 F 2 M – Statistical System for Forest Fire Management. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428831_53
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DOI: https://doi.org/10.1007/11428831_53
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