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
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