【摘要】 在建瓯设置 40块毛竹林标准地 ,分别测定了毛竹单株各部分干重与能量 ,建立了各部分生物量模型 ,并在此基础上 ,运用人工神经网络方法对毛竹林各组分能量进行估测 .结果表明 :毛竹林各组分秆、枝叶和地下部分的平均能量依次为 4.2 32 2 5× 10 8、9.2 2 95× 10 7和 1.76 43× 10 8kJhm-2 ,所占的比例分别为 6 1.32 %、13.11%和 2 5 .5 7% ;所建立的毛竹林秆、枝叶和地下部分各组分能量人工神经网络模型的平均模拟精度分别为 87.88%、82 .99%和 82 .95 % ,平均预测精度分别为 87.13%、81.32 %和 81.86 % .从而为揭示毛竹林生产潜力提供科学依据 .图 4表 7参 19更多还原

【Abstract】 Based on the data of Phyllostachys heterocycla cv. pubescens in Jianou,Fujian,the dry weight and energy of bamboo various parts were determined,their biomass models were built,and the artificial neural network was applied to estimate the energy of the different parts of Phyllostachys heterocycla cv. pubescens forest.The results showed that the energy of stem,branch and leaf,under9.2295ground part were 4.23225×10 8, 9.2295×10 7 and 1.7643×10 8 kJ hm -2 ,and their distributive proportion of energy were 61.32%, 13.11 % and 25.57%, respectively.The mean simulative accuracy of artificial neural models of stem,branch and leaf,underground part were 87.88%,82.99%and 82.95% respectively,and their predictive accuracy were 87.13%,81.32% and 81.86%, respectively.This paper provids a scientific basis in revealing the latent capacity of Phyllostachys heterocycla cv. pubescens forest. Fig 4, Tab 7, Ref 19更多还原