The BP models for predicting the forest resources, including wooded area prediction, stand volume prediction and age class structure prediction, are developed in this treatise.
本论文采用人工神经网络方法建立了基于人工神经网络的森林资源预测模型，包括有林地面积预测、活立木蓄积量预测、龄级结构预测BP网络模型。
参考来源 - 基于ANN的森林经营决策模型研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The key for increase estimate Precision of stand volume is to understand well the interior of forestry reflective spectrum.
提高我国南方山地森林蓄积量遥感估算精度的关键在于准确理解森林反射光谱的内涵。
But stand volume descents to a great extent, age class and stand density structure are maladjusted badly, and the number of stand growth is low.
但蓄积量大幅下降，林分的龄组、密度结构严重失调，林分生长量偏低。
Moreover, the application of angle-count cruising to calculating the stand volume, standard stock number, stand weight and stock number per unit area, is discussed.
本文探讨了角规测树法在测算毛竹林分蓄积量、标准株数、林分重量及单位面积株数中的应用。
应用推荐