Forest Fire Disaster Area Prediction Based on Genetic Algorithm and Support Vector Machine
被引:6
作者:
Xiao, Fang
论文数: 0引用数: 0
h-index: 0
机构:
NE Forestry Univ, Sch Forestry, Harbin 150040, Peoples R ChinaNE Forestry Univ, Sch Forestry, Harbin 150040, Peoples R China
Xiao, Fang
[1
]
机构:
[1] NE Forestry Univ, Sch Forestry, Harbin 150040, Peoples R China
来源:
TRENDS IN CIVIL ENGINEERING, PTS 1-4
|
2012年
/
446-449卷
关键词:
support vector machine;
parameter optimization;
time series;
forest fire disaster area;
D O I:
10.4028/www.scientific.net/AMR.446-449.3037
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
Forest fire disaster area prediction based on genetic algorithm and support vector machine is presented in the paper. Genetic algorithm is used to select appropriate parameters of support vector machine. Genetic algorithm can obtain the optimal solution by a series of iterative computations. The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data. The comparison of the forest fire disaster area forecasting results between the proposed GA-SVM model and the SVM model is given,which indicates that the proposed GA-SVM model has more excellent forest fire disaster area forecasting results than the SVM model.