Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Huanhuan Ba"'
Publikováno v:
Hydrology Research, Vol 52, Iss 6, Pp 1436-1454 (2021)
The conceptual hydrologic model has been widely used for flood forecasting, while long short-term memory (LSTM) neural network has been demonstrated a powerful ability to tackle time-series predictions. This study proposed a novel hybrid model by com
Externí odkaz:
https://doaj.org/article/14b194efae674491a95204e87b5a1154
Publikováno v:
Medicine; 7/5/2024, Vol. 103 Issue 27, p1-6, 6p
Publikováno v:
Hydrology Research, Vol 52, Iss 6, Pp 1436-1454 (2021)
The conceptual hydrologic model has been widely used for flood forecasting, while long short-term memory (LSTM) neural network has been demonstrated a powerful ability to tackle time-series predictions. This study proposed a novel hybrid model by com
Publikováno v:
Hydrology Research. 50:1751-1771
Quantifying forecast uncertainty is of great importance for reservoir operation and flood control. However, deterministic hydrological forecasts do not consider forecast uncertainty. This study develops a conditional probability model based on copula
Autor:
Huanhuan Ba, Shaokun He, Lele Deng, Chong-Yu Xu, Kebing Chen, Zhen Liao, Dimitri Solomatine, Shenglian Guo
Joint and optimal impoundment operation of the large-scale reservoir system has become more crucial for modern water management. Since the existing techniques fail to optimize the large-scale multi-objective impoundment operation due to the complex i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2b3b3eaaeb4dd7b33ac40c227889f0b
https://doi.org/10.5194/hess-2019-586
https://doi.org/10.5194/hess-2019-586
Publikováno v:
Hydrology Research. 49:1417-1433
Reservoir inflow forecasting is a crucial task for reservoir management. Without considering precipitation predictions, the lead time for inflow is subject to the concentration time of precipitation in the basin. With the development of numeric weath
Publikováno v:
Hydrology Research. 49:744-760
This study attempts to improve the accuracy of runoff forecasting from two aspects: one is the inclusion of soil moisture time series simulated from the GR4J conceptual rainfall–runoff model as (ANN) input; the other is preprocessing original data
Publikováno v:
Journal of Hydrology. 585:124760
As atmospheric moisture capacity is highly sensitive to rising temperatures, precipitation extremes are widely projected to intensify with a warming climate and thus altering the flooding generation regime. Previous works seldomly focused on bivariat
Accurate and robust multi-step-ahead flood forecast during flood season is extremely crucial to reservoir flood control. A modified hybrid learning algorithm, which fuses the Least Square Estimator (LSE) with Genetic Algorithm (GA), is proposed for o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7bda6afb4d3096e9084a8cc2ff59a5d
https://doi.org/10.5194/hess-2017-457
https://doi.org/10.5194/hess-2017-457
Autor:
Shaokun He, Shenglian Guo, Chong-Yu Xu, Kebing Chen, Zhen Liao, Lele Deng, Huanhuan Ba, Solomatine, Dimitri
Publikováno v:
Hydrology & Earth System Sciences Discussions; 3/17/2020, p1-48, 48p