摘要
在建立商品林投资风险评价指标体系的基础上,运用人工神经网络的建模方法,利用MATLAB神经网络工具箱,对实例进行了训练和预测,建立基于BP神经网络的商品林投资风险评估模型。对其检测发现,期望输出与实际输出的误差很小,说明该模型能较为准确地按照专家的评价方法进行工作,可以为商品林投资提供了现实可用的风险预测和评估工具,进一步显示出人工神经网络模型在现代商品林经济领域应用的广阔前景。
The paper proposed a multi-target synthetic evaluation system of commercial forest investment based on neural network,used Matlab Neural Network toolbox to train and predict factual examples and established risk evaluation model of commercial forest investment based on BP neural network that the error between desired output and actual output is small.The results show that back-propagation network model can carry on the work according to the experts methods,which provides the risk evaluation forecasting tool for commercial forest investment and demonstrates that the neural network model has boad application prospects in the modern forest economical domain.
出处
《林业经济》
北大核心
2010年第10期85-87,100,共4页
Forestry Economics
关键词
BP神经网络
商品林投资
风险评估
BP Neural Network
commercial forest investment
risk assessment
