Hydrological combined forecasting model based on Bayesian analysis

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作者
School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China [1 ]
机构
来源
Yingyong Jichu yu Gongcheng Kexue Xuebao | 2008年 / 2卷 / 287-295期
关键词
Bayesian networks - Drainage - Floods - Forecasting - Mathematical models - Monte Carlo methods - Rivers;
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摘要
Hydrological combined forecasting method can offer synthetical analysis to prediction results received from several separately forecasting models. Remarkably, as it showed the impression of weakness when facing absence of historical flood data for some drainage areas. A new combined forecasting in this paper was introduced, which was on the basis of Bayesian analysis, Experts' experience, MCMC, Gibbs sample and real-time emendation function. Finally, the precision of the Bayesian combined analysis model was validated by taking the drainage area of Nen River for instance. The result indicates the established model was feasible and practical, and its precision overwhelms any single model's precision.
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