TY - JOUR
T1 - Parallel dynamic data driven genetic algorithm for forest fire prediction
AU - Denham, Mónica
AU - Cortés, Ana
AU - Margalef, Tomás
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=70350436692&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-03770-2_40
DO - 10.1007/978-3-642-03770-2_40
M3 - Artículo
AN - SCOPUS:70350436692
SN - 0302-9743
SP - 323
EP - 324
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -