基于LM-BP神经网络的小班生长预测模型

The Growth Forecast Model of Subcompartment which Based on LM-BP neural network

为了实现小班逐年数据精准预测,使用LM-BP神经网络进行训练仿真,并用传统建模法与生长预测模型进行对比。结果表明:利用LM-BP神经网络法进行小班生长量模型训练精度高于传统方法,其训练方法简便易实施,可应用于森林资源调查工作中。

In order to achieve the subcompartment data accurate prediction year by year,the use of LM- BP neural network for training simulation,and comparing with traditional modeling method and growth forecast model,the results show that using LM- BP neural network training on subcompartment growth model has high precision than the traditional method,its training method is simple and easy to implement,so can be applied to forest resources investigation.