摘要
本文应用人工神经网络理论，对毛竹密度效应进行定量研究，建立了毛竹密度效应的三层前馈反向传播神经网络ＢＰ模型，仿真结果表明，人工神经网络模型能表征毛竹林分平均胸径、平均高度、密度对林分杆产量的映射效应，从而为毛竹密度效应研究提供了新方法。
The effect of varied bamboo ( Phyllostachys pubescens ) stand densities was studied, using the theory of artificial neural network. Several models predicting respectively the mean diameter in breast height (D), the mean height (H), and the total culm weight (W) as related to stand density (N) were generated on the basis of a three-layer feed-forward backscattering BP model. The simulation results indicated that these artificial neural network-based models can well represent the growth characteristics of the bamboo stand, thus bringing forward a new approach to the study of density effect of bamboo stands.
出处
《经济林研究》
1999年第4期1-4,共4页
Non-wood Forest Research
关键词
毛竹
密度效应
神经网络
模型
研究
Phyllostachys pubescens
Stand density effect
Artificial neural network.
