DocumentCode
2248097
Title
Artificial intelligence for forest fire prediction
Author
Sakr, George E. ; Elhajj, Imad H. ; Mitri, George ; Wejinya, Uchechukwu C.
Author_Institution
American Univ. of Beirut, Beirut, Lebanon
fYear
2010
fDate
6-9 July 2010
Firstpage
1311
Lastpage
1316
Abstract
Forest fire prediction constitutes a significant component of forest fire management. It plays a major role in resource allocation, mitigation and recovery efforts. This paper presents a description and analysis of forest fire prediction methods based on artificial intelligence. A novel forest fire risk prediction algorithm, based on support vector machines, is presented. The algorithm depends on previous weather conditions in order to predict the fire hazard level of a day. The implementation of the algorithm using data from Lebanon demonstrated its ability to accurately predict the hazard of fire occurrence.
Keywords
artificial intelligence; ecology; fires; forestry; support vector machines; artificial intelligence; fire hazard level; forest fire management; forest fire risk prediction algorithm; support vector machine; weather condition; Data mining; Equations; Fires; Prediction algorithms; Support vector machines; Weather forecasting; Forest Fire Prediction; Machine Learning; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics (AIM), 2010 IEEE/ASME International Conference on
Conference_Location
Montreal, ON
Print_ISBN
978-1-4244-8031-9
Type
conf
DOI
10.1109/AIM.2010.5695809
Filename
5695809
Link To Document