Position: Home > Articles > Application of SVM Method on the Prediction of Forest Fire Danger
Scientia Silvae Sinicae
2007,43
(10)
80-85
SVM方法在森林火险预测中的应用
作 者：
黄玉霞;许东蓓;蒲肃
单 位：
兰州中心气象台
关键词：
森林火险综合指数;支持向量机;森林火险预测;分类模型;回归估计
摘 要：
用归一化差分植被指数(NDVI)和空气相对湿度构造森林火险综合指数。将支持向量机(SVM)方法用于森林火险预报预测试验,利用气象资料和卫星遥感资料,建立甘肃省林区森林火险分类推理模型和回归推理模型,并进行相应的预报试验。结果显示:分类推理模型具有良好的预报能力,预报效果明显优于传统的逐步回归方法;回归推理模型预报效果与逐步回归方法相差无几。
译 名：
Application of SVM Method on the Prediction of Forest Fire Danger
作 者：
Huang Yuxia Xu Dongbei Pu Su(Lanzhou Central Meteorological Observatory Lanzhou 730020)
关键词：
forest fire integrated index(FI); support vector machine(SVM); prediction of forest fire disaster; classification model; regression estimation
摘 要：
The forest fire danger composite index(FI) is constructed by normalized difference vegetation index (NDVI) and the relative humidity. Support vector machine (SVM) methods used for forest fire forecasting prediction test. Using meteorological data and secondary planet remote sensing data, the classification illation model and regression illation model of forest fire were based. The forecasting test was progressed too. The results show that classification illation model has favorable prediction ability, its prediction effect is superior to successive regression technique. But there is little difference in prediction effect between the regression illation model and successive regression technique.
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