摘要
本文通过应用人工神经网络模型中的ＢＰ网络模型，对济宁市地下水水位变化规律进行了定量预测，并与线性回归模型的计算结果进行比较，证明ＢＰ网络模型的精度较高。
Grondwater level variation in Jining City has been quantitavively predicted by using BP networks of artificial neural networks. Its result was compared with the results obtained by linear regressive model, and it is verified that the precision of BP network is higher than that of linear regressive model.
出处
《水文地质工程地质》
CAS
CSCD
1999年第5期14-16,共3页
Hydrogeology & Engineering Geology
基金
国土资源部"水资源评价与管理系列模型"开放研究实验室资助
关键词
人工神经网络
线性回归模型
地下水
水位变化
artificial neural networks, linear regressive model, groundwater level.
