基于BP神经网络的马尾松立木生物量模型研究OA北大核心CSCDCSTPCD
Single-tree biomass modeling of Pinus massoniana based on BP neural network
以马尾松为例,探索并验证BP神经网络模型在立木生物量估测上的适用性.通过12种算法的筛选、输入变量和输出变量的确定以及隐层节点数的选择,确定最优的模型拓扑结构,构建单隐层BP神经网络模型；对比单输入变量与多输入变量模型、单输出变量与多输出变量模型,并分析模型的输入变量数和输出变量数对模型估测精度的影响；将优选BP模型与传统相对生长模型进行对比以验证BP模型的可行性.结果表明:1)最优BP模型LM-DH-8-WtWaWr的训练算法为Levenber…查看全部>>
The purpose of this study was to explore and verify the applicability of BP neural network model on the single-tree biomass estimation for Pinus massoniana. The optimal model had been built after the topology was determined through screening 12 algorithms and choosing the number of inputs, outputs and hidden nodes. To explain the impact of input variable number on the accuracy, double input BP model was compared with single one. Also, to explain the impact o…查看全部>>
王轶夫;孙玉军;郭孝玉
北京林业大学林学院北京林业大学林学院北京林业大学林学院
农业科技
BP神经网络立木生物量模型Levenberg-Marquardt算法马尾松
BP neural network single-tree biomass model Levenberg-Marquardt algorithm Pinus massoniana
《北京林业大学学报》 2013 (2)
17-21,5
林业公益性行业科研专项(200904003-1).
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