水电站入库径流量的灰色自记忆预测方法研究  

Gray Self-Memory Prediction of Inflow to Hydropower Station Reservoir

作　　者：李力[1] 沈冰[1] 李荣峰 赵长森[3] 

机构地区：[1]西安理工大学水利水电学院 [2]山西省水利水电科学研究院,山西太原030002 [3]中国科学院地理与资源研究所,北京100101

出　　处：《应用科学学报》2007年第2期198-201,共4页Journal of Applied Sciences

摘　　要：运用灰色系统理论与数据序列自记忆性原理相结合的方法,提出了数据序列预测的灰色自记忆模型,并应用于年径流量及汛期来水预测.山西沁河曹河水电站年径流及汛期径流预测的实例表明,该模型能处理非平稳数据序列并反映动态数据序列的极值趋势,可提高预测精度.Combining the theory of gray system with self-memory principle, a new model for predicting time series of reservoir inflow is proposed. The model has been used to predict the annual and flood period inflow to reservoir of Caohe Hydropower Station on the Jin River. The case study indicates that the model can deal with non-stationary time series and provide the inflow trend and extreme values with improved accuracy.

关 键 词：径流量 自记忆 灰色模型 预测 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]