摘要
本文以闽北地区马尾松造纸原料林调查资料为基础，应用人工神经网络理论，建立了马尾松造纸原料林密度调节的三层前馈反向传播神经网络模型．仿真结果表明该模型效果较理想。
On the basis of investigated data of the paper-making raw material forest of Pinus massoniana in the north of Fujian province, the paper builds a model of three-level feed toward back-propagation neural network to simulate density-dependent regulation of Pinus massoniana. The result of simulating shows that artificial neural network model is good, which can be used to conduct forest production.
出处
《福建林学院学报》
CSCD
1998年第4期298-300,共3页
Journal of Fujian College of Forestry
基金
福建省财政厅资助项目
关键词
人工神经网络
密度调节
马尾松
造纸原料林
artificial neural network, density-dependent regulation, Pinus massoniana, paper-making raw material forest
