关键词: 森林火焰, 最优阈值搜索法, 变步长, 小脑算术计算模型网络, 最小均方算法

Abstract: Concerning the defects of traditional fire recognition, a forest fire recognition system of Cerebella Model Articulation Controller (CMAC) network, which was based on variable step Least Mean Square (LMS) algorithm of hyperbolic secant, was presented. Through analyzing some initial static and dynamic characteristics, forest fire was preliminarily identified. And on the basis of image segmentation using the optimal threshold search method, the corresponding eigenvectors were extracted as the input of the improved CMAC network to detect and identify forest fire. The simulation results show that the improved method can accurately and efficiently identify flame.

Key words: forest fire, optimal threshold search method, variable step, Cerebella Model Articulation Controller (CMAC) network, Least Mean Square (LMS) algorithm