智能系统学报Issue(4)：339-343,5.DOI:10.3969/j.issn.1673-4785.2011.04.010
支持向量机与BP网络在火灾图像探测上的比较
Comparisons between a support vector machine and BP neural network for video image fire detection
摘要
Abstract
According to the theoretical differences between a back propagation ( BP) network and support vector machine ( SVM) in relation to fire detection, two kinds of video image fire detection methods based on a BP network and SVM, respectively, were constructed. Judging from color distribution of the flames, the objective regions were separated in both methods, and their shape features along with the changes in shape features were extracted as criteria. The performance of each method was compared and analyzed after conducting many experiments. The experimental results show that the SYM had a high convergence rate and needed fewer training samples. At the same time, fewer misjudgments of testing samples confirmed that the BP network was more suitable for solving complex internal mechanism problems due to its good mapping capability.关键词
火灾探测/形状特征/支持向量机/BP神经网络Key words
fire detection/ shape features/ SVM/ BP neural network分类
信息技术与安全科学引用本文复制引用
何世钊,杨宣访,陈晓娟..支持向量机与BP网络在火灾图像探测上的比较[J].智能系统学报,2011,(4):339-343,5.基金项目
国家自然科学基金资助项目(50721063). （50721063）
