Abstract
Fire propagation simulation is seen as a challenging problem in the area of simulation, due to the complexity of the physical models involved, the need for a great amount of computation and the difficulties of providing accurate input parameters. Input parameters appear as one of the major sources of deviation between predicted results and real-fire propagation. Evolutionary algorithms have been used to optimize the input parameters. However, such optimization techniques must be carried out during real-time operation and, therefore, certain methods must be applied to accelerate the optimization process. These methods take advantage of the computational power offered by distributed systems.
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Abdalhaq, B., Cortés, A., Margalef, T., Luque, E. (2004). Accelerating Optimization of Input Parameters in Wildland Fire Simulation. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2003. Lecture Notes in Computer Science, vol 3019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24669-5_138
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DOI: https://doi.org/10.1007/978-3-540-24669-5_138
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