DocumentCode :
2405163
Title :
An evolved fuzzy logic system for fire size prediction
Author :
Fowler, Alan ; Teredesai, Ankur M. ; De Cock, Martine
Author_Institution :
Inst. of Technol., Univ. of Washington, Tacoma, WA, USA
fYear :
2009
fDate :
14-17 June 2009
Firstpage :
1
Lastpage :
6
Abstract :
The accurate prediction of forest fire size is important in order to issue adequate and timely warnings and to allocate fire-fighting assets efficiently and effectively. A forest fire data set collected in Portugal has recently become available as a benchmark for experimental validation of data mining techniques to tackle this problem. In this paper, we explore the suitability of a fuzzy rule based system to solve the forest fire size prediction problem. Since we have no specific domain expertise, we evolve the fuzzy rules as well as the membership functions automatically using genetic algorithms. The results clearly demonstrate the utility of the evolved fuzzy rule based system.
Keywords :
data mining; fires; forestry; fuzzy logic; geography; knowledge based systems; data mining techniques; fire size prediction; fire-fighting assets; forest fire size; fuzzy logic system; fuzzy rule based system; genetic algorithms; membership functions; Data mining; Fires; Fuzzy logic; Fuzzy systems; Genetic algorithms; Humidity; Knowledge based systems; Meteorology; Temperature; Weather forecasting; co-evolution; forest fire; fuzzy rule base; genetic algorithm; meteorological data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 2009. NAFIPS 2009. Annual Meeting of the North American
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4244-4575-2
Electronic_ISBN :
978-1-4244-4577-6
Type :
conf
DOI :
10.1109/NAFIPS.2009.5156419
Filename :
5156419
Link To Document :
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