摘要
以农地分级标准作为基础样本,构建了径向基网络模型,并利用该网络进行了实际评价。结果表明:RBF网络计算精度高,简便有效,可操作性强,具有极快的收敛速度和分类能力,与其它方法比较,不需要烦琐的计算过程,节约了大量计算时间,并且RBF网络具有良好的泛化能力,适用性广,在土地资源评价中具有良好的应用前景。
According to the basis of the agriculture land classification, a radial basis function network could be constructed, which was one of the artificial neural networks.Tne authors used this model to evaluate the land quality.Practice showed that the result had better precision and reliability comparing with other methods. With its fast convergence speed and good classification capability, RBF- ANN was convenient in operation and could save a lot of time. It had good extensive ability and took on wide application foreground in land resources assessment.
出处
《资源开发与市场》
CAS
CSSCI
2008年第9期786-788,共3页
Resource Development & Market
基金
2007四川省基本科研业务费