TY - JOUR
T1 - Accelerating wildland fire prediction on cluster systems
AU - Cortes Fite, Ana
AU - Luque Fadon, Emilio
AU - Margalef Burrull, Tomas Manuel
AU - Abdalhaq, Baker
PY - 2004/12/1
Y1 - 2004/12/1
N2 - Classical prediction fire schemes do not match the real fire propagation, basically, because of the complexity of the physical models involved, the need for a great amount of computation and the difficulties of providing accurate input parameters. We describe an enhanced prediction scheme, which uses recent fire history and optimization techniques to predict near future propagation. The proposed method takes advantage of the computational power offered by distributed systems to accelerate the optimization process at real time. © Springer-Verlag Berlin Heidelberg 2004.
AB - Classical prediction fire schemes do not match the real fire propagation, basically, because of the complexity of the physical models involved, the need for a great amount of computation and the difficulties of providing accurate input parameters. We describe an enhanced prediction scheme, which uses recent fire history and optimization techniques to predict near future propagation. The proposed method takes advantage of the computational power offered by distributed systems to accelerate the optimization process at real time. © Springer-Verlag Berlin Heidelberg 2004.
U2 - 10.1007/978-3-540-24687-9_28
DO - 10.1007/978-3-540-24687-9_28
M3 - Article
VL - 3037
SP - 220
EP - 227
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -