期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2011
卷号：34
期号：1
页码：029-033
出版社：Journal of Theoretical and Applied
摘要：The explosive growth of spatial data and extensive utilization of spatial databases [1] emphasize the necessity for the automated discovery of spatial knowledge. In modern times, spatial data mining has emerged as an area of huge research. Forest fires are a chief green concern, causing inexpensive and environmental damage while endangering human lives across the world. The fast or early detection of forest fires [2] is a essential element for controlling such phenomenon. The application of remote sensing is at present a significant method for forest fires monitoring [3], particularly in vast and remote areas. This paper presents an intelligent system to detect the presence of forest fires in the forest spatial data using SMO and Artificial Neural Networks. Extensive experimental assessments on publicly available spatial data illustrated the efficiency of the proposed system in effectively detecting forest fires. Finally, since large fires are rare dealings, outlier detection techniques will also be addressed.
关键词：Spatial Data Mining; Forest Fire Data; SMO; ANN
