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- W2364731296 abstract "Flood forecasting is an important component of flood control and waterlogged drainage planning and flood dispatching in a river network region.As a computation foundation of flood forecasting,hydro dynamic model is restricted and affected by many factors.Sometimes,we need to adopt a certain kind of technique to correct them when big errors are observed between the water level simulated by the hydro dynamic model and the observed data.In this paper,this kind of error series are first analyzed,and then the autoregressive model combining with memory attenuated recursive least square(RLS) algorithm is applied,and lastly they were validated with corresponding tests.Moreover,the results of simulating the three segments of flood taking place in the study area indicate that the correction technique can enhance computation precision effectively.It means that this technique can be used for forecasting floods of the river networks." @default.
- W2364731296 created "2016-06-24" @default.
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- W2364731296 date "2009-01-01" @default.
- W2364731296 modified "2023-09-28" @default.
- W2364731296 title "Application of Correction Technique by Autoregressive Model with Memory Attenuated RLS Algorithm on Flood Forecasting of a River Network" @default.
- W2364731296 hasPublicationYear "2009" @default.
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