Han Wang
Hohai University
12 Papers
15 Citations
Han Wang is an academic researcher from Hohai University. The author has contributed to research in topics: Flood myth & Computer science. The author has an hindex of 2, co-authored 9 publications.
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Papers
Risk analysis for reservoir flood control operation considering two-dimensional uncertainties based on Bayesian network
TL;DR: A risk analysis model for reservoir flood regulation under two-dimensional uncertainties based on Bayesian network is proposed, which is able to conduct bi-directional inferences and infer the probability distribution of any other node, which has practical value for risk assessment and control of reservoir flood control operation.
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Spark-based parallel dynamic programming and particle swarm optimization via cloud computing for a large-scale reservoir system
TL;DR: This study proposes the spark-based parallel dynamic programming (SPDP) and spark- based parallel particle swarm optimization (SPPSO) methods via parallel cloud computing, which ensures the global search capability of the algorithm.
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Multi-objective risk analysis for flood control operation of a complex reservoir system under multiple time-space correlated uncertainties
TL;DR: Wang et al. as mentioned in this paper introduced the initial water level uncertainty to risk analysis for multi-reservoir operation and established a risk analysis model for multiobjective flood control operation of a complex reservoir system coupling multi-dimensional uncertainties.
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Stochastic programming for floodwater utilization of a complex multi-reservoir system considering risk constraints
TL;DR: In this paper, a risk-based aggregation-decomposition method for floodwater utilization of a complex multi-reservoir system is proposed, where the original system is decomposed into four basic configurations, and the upper bound of FLWL of each reservoir is identified based on a given risk level for the subsystem and risk hedging between reservoirs.
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A comparison of the reproducibility of regional precipitation properties simulated respectively by weather generators and stochastic simulation methods
TL;DR: Wang et al. as mentioned in this paper used the precipitation records from 1958 to 2011 at nine meteorological stations within Huaihe River System in Henan Province to evaluate a stochastic hydrological simulation method, SARIMA model, and two types of weather generators, through the comparison of statistical characteristics regarding precipitation variables, such as mean, mean square error, extreme value and coefficient of variation.
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