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毛竹林各组分能量估算模型的研究
引用本文:何东进,洪伟,吴承祯.毛竹林各组分能量估算模型的研究[J].应用与环境生物学报,2000,6(5):412-418.
作者姓名:何东进  洪伟  吴承祯
作者单位:福建林学院资源与环境系南平 353001
基金项目:福建省自然科学基金资助项目(C96027)
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4.23225×10

关 键 词:毛竹  组分  能量  人工神经网络  估算
修稿时间:2000年2月24日

STUDY ON E NERGY ESTIMATION MODELS FOR VARIOUS PARTS OF PHYLLOSTACHYS HETEROCYCLA CV. PUBESCENS FOREST
He Dongjin,HONG Wei,WU Chengzhen.STUDY ON E NERGY ESTIMATION MODELS FOR VARIOUS PARTS OF PHYLLOSTACHYS HETEROCYCLA CV. PUBESCENS FOREST[J].Chinese Journal of Applied and Environmental Biology,2000,6(5):412-418.
Authors:He Dongjin  HONG Wei  WU Chengzhen
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 bi omass models were built,and the artificial neural network was applied to estima te the energy of the different parts of Phyllostachys heterocycla cv. pube scens forest.The results showed that the energy of stem,branch and leaf,und er9.2295ground part were 4.23225×108, 9.2295×107 and 1.7643×108 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 o f stem,branch and leaf,underground part were 87.88%,82.99%and 82.95% respect ively,and their predictive accuracy were 87.13%,81.32% and 81.86%, respectivel y.This paper provids a scientific basis in revealing the latent capacity of Phyllost achys heterocycla cv. pubescens forest. Fig 4, Tab 7, Ref 19
Keywords:Phyllostachys heterocycla  cv    pubescens  various parts  energy  artificial neural network  estimation  
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