A sequential Bayesian approach for hydrologic model selection and prediction
نویسندگان
چکیده
منابع مشابه
A sequential Bayesian approach for hydrologic model selection and prediction
[1] When a single model is used for hydrologic prediction, it must be capable of estimating system behavior accurately at all times. Multiple-model approaches integrate several model behaviors and, when effective, they can provide better estimates than that of any single model alone. This paper discusses a sequential model fusion strategy that uses the Bayes rule. This approach calculates each ...
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Kuo-Lin Hsu Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine CA 92697-2175, USA Tel.: +1 949 824 8826 Fax: +1 949 824 8831 E-mail: [email protected] Sequential Monte Carlo (SMC) methods are known to be very effective for the state and parameter estimation of nonlinear and non-Gaussian systems. In this study,...
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ژورنال
عنوان ژورنال: Water Resources Research
سال: 2009
ISSN: 0043-1397
DOI: 10.1029/2008wr006824