水利水电科技进展2017，Vol.37Issue(2)：73-77,5.DOI:10.3880/j.issn.1006-7647.2017.02.013
基于集合卡尔曼滤波的实时校正方法
A real-time alternating updating method based on ensemble Kalman filter
摘要
Abstract
To reduce the uncertainty in calculation of unsteady flows, a multivariate alternate updating method is proposed based on the ensemble Kalman filter. This method updates water stage and discharge data alternately to calibrate unsteady flow, using the observed information without the large matrix calculating;meanwhile, scaling transformation is used in order to improve the water level filter precision. Numerical experiments emphatically investigate the effects of measurement accuracy and water level transformation coefficient on forecast precision of the method. The results show that the forecast error increases as the measurement accuracy decreases;the water level transformation coefficient can obviously improve the effect of the multivariate alternate updating method, the larger the water level transformation coefficient is, the higher the forecast precision will be; the multivariate alternate updating method has good calibrating performance and can improve forecast accuracy of unsteady flows in open channel.关键词
水动力学模型/集合卡尔曼滤波/非恒定流/实时校正技术/洪水预报Key words
hydrodynamic model/ensemble Kalman filter/unsteady flow/real-time updating/flood forecasting分类
建筑与水利引用本文复制引用
顾炉华,赖锡军..基于集合卡尔曼滤波的实时校正方法[J].水利水电科技进展,2017,37(2):73-77,5.基金项目
水体污染控制与治理科技重大专项(2012ZX07101-011) （2012ZX07101-011）
国家自然科学基金(51379059,51279047) （51379059,51279047）
