降雨条件下蒙古栎和樟子松林地表死可燃物含水率预测方法的修正与比较
Influence of the Mixed Modes of Larch and Birch on Soil Faunal Community in Mountain Area of Northern Hebei,China
[目的]分析降雨条件对地表细小死可燃物含水率(FFMC)的影响,分别建立机器学习模型和传统模型对降雨条件下的可燃物含水率进行预测,并对所建立的预测模型进行评价和比较。[方法]选择东北地区典型阔叶树种蒙古栎和针叶树种樟子松,以其地表细小死可燃物作为研究对象,通过进行室内模拟降雨实验探究降雨对地表可燃物含水率的影响,分别采用直接估计法和卷积神经网络(CNN)构建预测模型,并结合野外实验数据对直接估计法所得模型进行修正,最终进行比较分析。[结果]与未经…查看全部>>
[Objective]Analyze the impact of rainfall conditions on the moisture content of surface fuel moisture content(FMC),establish machine learning models and traditional models to predict the moisture content of surface fuel under rainfall conditions,and evaluate and compare the established prediction models.[Method]Selecting the broad-leaved forest Quercus mongolica and coniferous forest Pinus sylvestris var.mongolica in northeast China,surface dead fine fuel as…查看全部>>
胡同欣;马灵感;高源廷;范佳乐;孙龙;
Fine fuel moisture content Prediction models Direct estimation method Convolutional neural networks
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