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Dynamic Data Driven Application for Forest Fire Spread Prediction
Abstract
This work describes a two stages prediction method for wildland fire growth prediction. Proposed method takes advantege of genetic algorithms in order to develope a high performance and scalable application.
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References
[1] Bevins C., ”FireLib User Manual and Technical Reference”. http://www.re.org/downloads/fireLib/1.0.4/relib.pdf. Acceded on January 2006.
[2] Darema, F. ”Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements.” ICCS 2004, LNCS 3038, Springer Berlin / Heidelberg, pp. 662-669.
[3] Rothermel R., ”A mathematical model for predicting re spread in wildland fuels”. USDA FS, Ogden TU, Res. Pap. INT-115, 1972.
[2] Darema, F. ”Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements.” ICCS 2004, LNCS 3038, Springer Berlin / Heidelberg, pp. 662-669.
[3] Rothermel R., ”A mathematical model for predicting re spread in wildland fuels”. USDA FS, Ogden TU, Res. Pap. INT-115, 1972.
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Published
2012-08-01
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How to Cite
[1]
“Dynamic Data Driven Application for Forest Fire Spread Prediction”, JCS&T, vol. 12, no. 02, pp. p. 84–86, Aug. 2012, Accessed: May 12, 2026. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/658
