摘要
根据西北干旱区地下水位周期性变化趋势明显的特点 ,提出了测井水位预报的季节型神经网络模型。同时 ,针对系列不同周期内变幅各异的特点 ,对监测序列进行了光滑处理。预报结果表明 :该模型预测效果较好 ,运行合理 ,对规律性不强的地下水位动态预报具有一定的实用价值。
Based on the neural network model of time series and the periodical changing characteristic of the groundwater level in dry region, a seasonal artificial neural network forecast model is set up At the same time the data smoothing process is carried out aimed at the different fluctuation during different period before these data are used for training The prediction results indicate that the model is reasonable, its accuracy is better, and has some practical value when being used in the dynamic groundwater level analysis
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2002年第4期473-477,共5页
Advances in Water Science
关键词
区域
地下水位
预报
季节型神经网络模型
周期
region
groundwater level
seasonal artificial neural network model
prediction
period
