兴安落叶松林地表可燃物含水率预测模型的研建

对大兴安岭落叶松林地表可燃物含水率影响因子进行分析,选取主要的环境因子,为该区域内林火管理工作提供重要的理论依据。利用软件SPSS Clementine12.0,将相对湿度、地表温度、空气温度作为输入神经元,将兴安落叶松林地表可燃物含水率作为神经网络输出神经元,建立基于BP神经网络的含水率模型。应用BP神经网络模型敏感度分析结果来评定环境因子对兴安落叶松林地表可燃物含水率影响的大小,分析表明,影响兴安落叶松林地表可燃物含水率的主要环境因子由小到大排序为:相对湿度、地表温度、空气温度。构建的兴安落叶松林地表可燃物含水率BP神经网络模型对该区域内的林火管理工作具有一定的借鉴意义。

Development of Xing,an Larch Forest Land Surface Fuel Moisture Rate Prediction Model

The surface fuel moisture rate influencing factors in Xing＇an larch forest land are analyzed,with main environmental factors selected as important theoretical basis for forest fire management in this area. Using the software SPSS Clementine12. 0,with relevant humidity,ground surface temperature and air temperature as input neurons to establish a moisture rate model based on BP neural network. The sensitivity analysis result of the BP neutral network is used to assess the effect of environmental factors on the surface fuel moisture rate in Xing＇an larch forest land. The analysis shows that the main environmental factors influencing the surface fuel moisture rate in Xing＇an larch forest land are relevant humidity,ground surface temperature and air temperature in the order of influence degree from strong to weak. The BP neutral network model for e surface fuel moisture rate in Xing＇an larch forest land constructed in this article is of certain reference for forest fire management work in this area.