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基于数据分析技术的水文组合预报应用研究

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Date of Publication:2007-01-01

Journal:大连理工大学学报

Affiliation of Author(s):建设工程学部

Issue:2

Page Number:246-251

ISSN No.:1000-8608

Abstract:Hydrological combined forecasting is a method giving summary and analysis to different forecasting results, produced by different predication models. Aiming at the two situations-abundance or lack of history flood data, the combined forecasting models separately based on multi-objective fuzzy optimization theory and Bayesian analysis theory are proposed correspondingly. The former model introduces multi-objective fuzzy optimization theory to find out optimal relative membership degree of each projection on some precision at different discharges, and then by means of weighted average to confirm the optimal forecasting result; the latter model is based on Bayesian theory, combined with experts' experiences, MCMC simulation, Gibbs sampling and real-time auto-tuning technology. Taking the drainage area of Nenjiang for instance, the precision of the two integrated models was tested, and the result indicates that the established models are available and practical, with higher precision than that of any single model.

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