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Prediction of Stand Diameter Distribution with Artificial Neural Network

机译:用人工神经网络预测林分直径分布

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An artificial neural network model forecasting diameter distribution of stands was created by using artificial neural network modeling technology, in Masson pine planted forest. Through training and optimum seeking, the idea model was created, in which the model structure is 3:6:6:1, the training error is 0.000281, and the total fitting accuracy is 98 %. Concretely, the mean frequency fitting accuracy of 82 training plots and its cumulated frequency fitting accuracy is 87 % and 98 %, respectively. While the mean frequency fitting accuracy of 18 testing plot and its cumulated frequency fitting accuracy is 88 % and 98%, respectively. The created model has very high fitting accuracy and very strong prediction ability so that it can be used in Masson pine planted forest from 10 to 30 years of age. The results indicate the artificial neural network technology can be applied in modeling diameter distribution of trees.
机译:利用人工神经网络建模技术,在马森松人工林中建立了预测林分直径分布的人工神经网络模型。通过训练和最优寻找,建立了思想模型,模型结构为3:6:6:1,训练误差为0.000281,总拟合精度为98%。具体而言,82个训练图的平均频率拟合精度及其累计频率拟合精度分别为87%和98%。 18个测试图的平均频率拟合精度及其累计频率拟合精度分别为88%和98%。所创建的模型具有非常高的拟合精度和非常强的预测能力,因此可以在10至30岁的Masson松树人工林中使用。结果表明,人工神经网络技术可以应用于树木直径分布的建模。

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