RoughSet-NN模型在林业信息处理上的应用

Application of RoughSet-NN Model in Forecast Information Processing

运用计算机技术解决林业问题成为数字农业的一个热点研究领域,融合了粗糙集和神经网络的各自优势,利用粗糙集可以减少信息表达的属性数量,使用神经网络方法系统具有较强的容错及抗干扰能力,为处理不确定、不完整信息提供了一条解决方法,因此,将粗糙集约简技术和神经网络方法结合进行应用,建立了RoughSet-NN模型,并将该模型对给定立地条件的杨树生长状况进行预测。实验表明,该方法收敛,预测准确度高。

It is clear that computer based technique and computer technology used in solving agriculture＇ s and forestry＇ s matter are a focus these day. Combines roughset and neural networks, and builds a RoughSet - NN model. Roughset can reduce the number of attribute, and neual networks have the ability of fault tolerant and anti - jamming. Forecast the arbor growth with this model, and the experimental results indicate the method is convergent and has a high degree of certainty.