Bayesian-combined wavelet regressive modeling for hydrologic time series forecasting
文献类型：SCI/SSCI论文
| 作者 | Sang Y. F. ; Shang L. Y. ; Wang Z. G. ; Liu C. M. ; Yang M. G. |
| 发表日期 | 2013 |
| 关键词 | hydrologic time series forecasting wavelet regression model Bayesian theory probabilistic forecasting predictability artificial neural-networks uncertainty assessment decomposition prediction |
| 英文摘要 | Wavelet regression (WR) models are used commonly for hydrologic time series forecasting, but they could not consider uncertainty evaluation. In this paper the AM-MCMC (adaptive Metropolis-Markov chain Monte Carlo) algorithm was employed to wavelet regressive modeling processes, and a model called AM-MCMC-WR was proposed for hydrologic time series forecasting. The AM-MCMC algorithm is used to estimate parameters' uncertainty in WR model, based on which probabilistic forecasting of hydrologic time series can be done. Results of two runoff data at the Huaihe River watershed indicate the identical performances of AM-MCMC-WR and WR models in gaining optimal forecasting result, but they perform better than linear regression models. Differing from the WR model, probabilistic forecasting results can be gained by the proposed model, and uncertainty can be described using proper credible interval. In summary, parameters in WR models generally follow normal probability distribution; series' correlation characters determine the optimal parameters values, and further determine the uncertain degrees and sensitivities of parameters; more uncertain parameters would lead to more uncertain forecasting results and hard predictability of hydrologic time series. |
| 出处 | Chinese Science Bulletin |
| 卷 | 58 |
| 期 | 31 |
| 页 | 3796-3805 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1001-6538 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/30288]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Sang Y. F.,Shang L. Y.,Wang Z. G.,et al. Bayesian-combined wavelet regressive modeling for hydrologic time series forecasting. 2013. |
入库方式： OAI收割
来源：地理科学与资源研究所
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