摘要
本文以影响毛竹生长的6个主要气象因子为输入变量，以毛竹平均胸径为输出变量，首次运用人工神经网络方法建立毛竹生长动态模拟预测模型。结果表明：该模型模拟精度高达93．91％，从而为人工神经网络方法的应用和毛竹科学研究开辟新的思路。
The artificial neural netowrk was firstly applied in building the simulative. and predictive model of growth dynamic of Phyllostachys pubescens, with the year's averag temperature,the highest annual temperature,accumulated temperature above 10℃, yearly rainfall,relative humidity and rainfall amount during sprouting as factors. The results indicated that the accuracy of the prediction model was as high as 93. 91%, and it opened up a new application of artificial neural network in the study of Ph. pubescens.
出处
《竹子研究汇刊》
北大核心
1998年第3期32-36,共5页
Journal of Bamboo Research
关键词
毛竹
生长
动态模拟
预测模型
Phyllostachys pubescens
Artificial neural network
Simulation and prediction
