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水文预报与水资源优化管理技术
deep learning for recovering terrestrial water storage from gravity and altimetry
measurements[J]. Geophysical Research Letters,2020,47(17).
[8] NALLEY D,ADAMOWSKI J,KHALIL B,et al. A comparison of conventional
and wavelet transform based methods for streamflow record extension[J].
Journal of Hydrology,2020(582):124503.
[9] ALI M,PRASAD R,XIANG Y,et al. Complete ensemble empirical mode
decomposition hybridized with random forest and kernel ridge regression model
for monthly rainfall forecasts[J]. Journal of Hydrology,2020(584):124647.
[10] WU H,YANG Q,LIU J,et al. A spatiotemporal deep fusion model for
merging satellite and gauge precipitation in China[J]. Journal of Hydrology,
2020,584(2006): 124664.
[11] ORLAND E,ROERING J J,THOMAS M A,et al. Deep Learning as a tool
to forecast hydrologic response for landslide-prone hillslopes[J]. Geophysical
Research Letters,2020,47(16).
[12] PANAHI M,SADHASIVAM N,POURGHASEMI H R,et al. Spatial
prediction of groundwater potential mapping based on convolutional neural
network(CNN)and support vector regression(SVR)[J]. Journal of
Hydrology,2020(588):125033.
[13]段雅楠,梁忠民,赵建飞,仇知雨,李彬权 . 基于 Stacking 集成框架的水文
模型组合预报研究[J]. 水电能源科学,2022,40(09):27-30+39.DOI:
10.20040/j.cnki.1000-7709.2022.20212422.
[14]王忠义,崔东文 . 基于小波包分解 - 非洲秃鹫优化算法 - 深度极限学习机的
水文预报模型及其应用[J]. 水电能源科学,2022,40(08):26-31.
[15]欧阳文宇,叶磊,王梦云,孟子文,张弛 . 深度学习水文预报研究进展综述
Ⅰ——常用模型与建模方法[J]. 南水北调与水利科技(中英文),2022,
20(04):650-659.
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