摘要
针对黄河中游吴堡—龙门区间泥沙量过程的特点,基于统计模型方法,建立了多输入、单输出的龙门站含沙量过程预报方案,采用逐步回归方法进行预报因子筛选和模型率定,结合最小二乘递推算法的实时校正技术对含沙量过程进行预报,并根据实测资料对预报方案进行了检验。结果表明,该统计预报方案精度较高、适用性较好。
According to the characteristics of sediment concentration process in region between Wubao and Longmen of middle reaches of the Yellow River, multi-input and single-output forecasting scheme of Longmen sediment concentra- tion process is established with statistical model. The stepwise regression method is used to select predictor and calibrate model. Real-time correction technique with least squares recursive method is applied to forecast sediment concentration process. The forecasting scheme is verified with observation data. The results show that the statistical forecasting scheme has high accuracy and good applicability.
出处
《水电能源科学》
北大核心
2012年第4期83-86,共4页
Water Resources and Power
基金
水利部公益性行业科研专项经费基金资助项目(200901016)
江苏高校优势学科建设工程基金资助项目
关键词
含沙量
统计预报
逐步回归
最小二乘递推
黄河中游
sediment concentration
statistical forecast
stepwise regression
least square recursion
middle reachesof Yellow River
