基于人工神经网络的林分直径分布预测

以马尾松人工林为研究对象,用人工神经网络建模技术构建了林分直径分布预测模型。经训练和优选,得到的理想模型结构为3∶6∶6∶1,训练误差指标为0.000281,总体拟合准确度为98%。模型对82块训练标准地的累积频率拟合准确度最大为100%,最小为95%,平均为98%;频率拟合准确度最大为96%,最小为75%,平均为87%。模型对18块检验标准地的累积频率预测准确度最大为99%,最小为97%,平均为98%;频率预测准确度最大为96%,最小为76%,平均为88%。所建模型具有很好的拟合效果和很强的预测能力,可用于10～30年生马尾松人工林。研究结果证明,人工神经网络技术可以作为有效的林分直径分布预测技术。

Forecasting stand diameter distribution based on artificial neural network

A stand diameter distribution model was described by using artificial neural network modeling technology,in a Masson pine forest.By training and optimization,an ideal model was developed,with a model structure of 3:6:6:1,a training error of 0.000281 and a 98% accurate fit.For the 82 training plots,the accuracy of accumulated frequency fitting ranged from 95% to 100%,with a mean of 98%.The accuracy of frequency fitting ranged from 75% to 96%,with a mean of 87%.For the 18 test plots,the accuracy of accumulate...