Title :
Forest fire prediction and management using soft computing
Author_Institution :
Dept. of Comput. Sci., Univ. of Castilla-La Mancha, Ciudad Real, Spain
Abstract :
The problem of assigning and optimizing resources is a constant in the daily fight against forest fires in the Mediterranean Area and is due to the frequency and simultaneity of the fires together with the limited resources available. Thus, it seems necessary to predict the evolution of the forest fire occurrence-danger rate for a given area in the short and medium term. In order to satisfy this real prediction need, it is presented INCEND-IA: A KBS for prediction and decision support in fighting against forest fires.
Keywords :
data mining; decision support systems; fires; forestry; geographic information systems; knowledge based systems; neural nets; INCEND-IA knowledge-based system; KBS; Mediterranean Area; forest fire occurrence-danger rate; forest fire prediction; soft computing; Computer architecture; Computer science; Fires; Geographic Information Systems; Information management; Knowledge acquisition; Knowledge based systems; Prototypes; Resource management; Spatial databases;
Conference_Titel :
Industrial Informatics, 2003. INDIN 2003. Proceedings. IEEE International Conference on
Print_ISBN :
0-7803-8200-5
DOI :
10.1109/INDIN.2003.1300349
