Review of machine learning-based surrogate models of groundwater contaminant modeling
J Luo, X Ma, Y Ji, X Li, Z Song, W Lu - Environmental Research, 2023 - Elsevier
Heavy computational load inhibits the application of groundwater contaminant numerical
model to groundwater pollution source identification, remediation design, and uncertainty …
model to groundwater pollution source identification, remediation design, and uncertainty …
Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review
During the last three decades, the water resources engineering field has received a
tremendous increase in the development and use of meta-heuristic algorithms like …
tremendous increase in the development and use of meta-heuristic algorithms like …
Data‐worth analysis for heterogeneous subsurface structure identification with a stochastic deep learning framework
Reliable characterization of subsurface structures is essential for earth sciences and related
applications. Data assimilation‐based identification frameworks can reasonably estimate …
applications. Data assimilation‐based identification frameworks can reasonably estimate …
Stage‐wise stochastic deep learning inversion framework for subsurface sedimentary structure identification
The stochastic models and deep‐learning models are the two most commonly used
methods for subsurface sedimentary structures identification. The results from the stochastic …
methods for subsurface sedimentary structures identification. The results from the stochastic …
An integrated framework of deep learning and entropy theory for enhanced high-dimensional permeability field identification in heterogeneous aquifers
Accurately estimating high-dimensional permeability (k) fields through data assimilation is
critical for minimizing uncertainties in groundwater flow and solute transport simulations …
critical for minimizing uncertainties in groundwater flow and solute transport simulations …
Integration of deep learning and information theory for designing monitoring networks in heterogeneous aquifer systems
Groundwater monitoring networks are direct sources of information for revealing subsurface
system dynamic processes. However, designing such networks is difficult due to …
system dynamic processes. However, designing such networks is difficult due to …
Optimizing effluent trading and risk management schemes considering dual risk aversion for an agricultural watershed
J Zhang, Y Li, L You, G Huang, X Xu, X Wang - Agricultural Water …, 2022 - Elsevier
Increasing amounts of wastewater are discharged to water bodies, with a risk of exceeding
their capacity to cope with such loads. Nutrient discharge forms two types of risk, ie …
their capacity to cope with such loads. Nutrient discharge forms two types of risk, ie …
Machine learning-based optimal design of groundwater pollution monitoring network
Y **ong, J Luo, X Liu, Y Liu, X **n, S Wang - Environmental Research, 2022 - Elsevier
It is an important task of environmental management to design groundwater pollution
monitoring network (GPMN) to find out the occurrence of pollution events and carry out …
monitoring network (GPMN) to find out the occurrence of pollution events and carry out …
Approximating robust Pareto fronts by the MEOF-based multiobjective evolutionary algorithm with two-level surrogate models
The multiobjective optimization problems (MOPs) under uncertain environments are very
challenging to be solved due to the sensitivities of some robust decision variables. To find …
challenging to be solved due to the sensitivities of some robust decision variables. To find …
Bayesian ensemble machine learning-assisted deterministic and stochastic groundwater DNAPL source inversion with a homotopy-based progressive search …
J Bian, D Ruan, Y Wang, X Sun, Z Gu - Journal of Hydrology, 2023 - Elsevier
A hyperheuristic homotopy algorithm (HH-HA) and a homotopy-based swarm intelligence
algorithm for parallel stochastic search are proposed to improve the search ergodicity and …
algorithm for parallel stochastic search are proposed to improve the search ergodicity and …