Groundwater contaminant source identification based on an ensemble learning search framework associated with an auto xgboost surrogate
Z Pan, W Lu, H Wang, Y Bai - Environmental Modelling & Software, 2023 - Elsevier
Groundwater contaminant source identification (GCSI) is commonly accompanied by search
process which tweaks the unknown contaminant source information to match the simulation …
process which tweaks the unknown contaminant source information to match the simulation …
Identifying groundwater contamination sources based on the hybrid grey wolf gradient algorithm and deep belief neural network
J Li, Z Wu, H He, W Lu - Stochastic Environmental Research and Risk …, 2023 - Springer
The simulation optimization (S/O) method is widely used in the identification of groundwater
contamination sources (IGCSs). However, in most cases, the IGCSs has the characteristics …
contamination sources (IGCSs). However, in most cases, the IGCSs has the characteristics …
Groundwater contamination source identification based on a hybrid particle swarm optimization-extreme learning machine
J Li, W Lu, H Wang, Y Fan, Z Chang - Journal of Hydrology, 2020 - Elsevier
When the simulation-optimization method is applied to groundwater contamination source
identification (GCSI), the numerical simulation model is usually embedded in the …
identification (GCSI), the numerical simulation model is usually embedded in the …
Application of mixed-integer nonlinear optimization programming based on ensemble surrogate model for dense nonaqueous phase liquid source identification in …
Z Hou, Z Dai, W Lao, Y Wang, W Lu - Environmental Engineering …, 2019 - liebertpub.com
Groundwater contamination source identification (GCSI) is critical for taking effective
measures to protect groundwater resources, assess risks, mitigate disasters, and design …
measures to protect groundwater resources, assess risks, mitigate disasters, and design …
An iterative updating heuristic search strategy for groundwater contamination source identification based on an ACPSO–ELM surrogate system
H Wang, W Lu, Z Chang - Stochastic Environmental Research and Risk …, 2021 - Springer
The simulation-random statistics (SRS) method is one of the effective approaches to solving
groundwater contamination source identification (GCSI) challenges. In this paper, we …
groundwater contamination source identification (GCSI) challenges. In this paper, we …
Groundwater contamination source identification based on Sobol sequences–based sparrow search algorithm with a BiLSTM surrogate model
Y Ge, W Lu, Z Pan - Environmental Science and Pollution Research, 2023 - Springer
In the traditional linked simulation–optimization method, solving the optimization model
requires massive invoking of the groundwater numerical simulation model, which causes a …
requires massive invoking of the groundwater numerical simulation model, which causes a …
A combined search method based on a deep learning combined surrogate model for groundwater DNAPL contamination source identification
Z Wang, W Lu, Z Chang, J Luo - Journal of Hydrology, 2023 - Elsevier
Abstract Ensemble Kalman filter (EnKF) and optimization methods are two mainstream
methods in groundwater contamination source identification, but most researchers usually …
methods in groundwater contamination source identification, but most researchers usually …
A differential evolutionary Markov chain algorithm with ensemble smoother initial point selection for the identification of groundwater contaminant sources
Z Chang, W Lu, Z Wang - Journal of Hydrology, 2021 - Elsevier
Groundwater contaminant source identification (GCSI) can provide support for the
confirmation of responsibility and the remediation of pollution. This study has developed an …
confirmation of responsibility and the remediation of pollution. This study has developed an …
Groundwater contaminated source estimation based on adaptive correction iterative ensemble smoother with an auto lightgbm surrogate
Z Pan, W Lu, Y Bai - Journal of Hydrology, 2023 - Elsevier
In this work, we have proposed an adaptive-correction iterative ensemble smoother (ACIES)
to adaptively adjust the range of unknown variables, for improving the estimation accuracy …
to adaptively adjust the range of unknown variables, for improving the estimation accuracy …
Groundwater contamination source identification using improved differential evolution Markov chain algorithm
Y Bai, W Lu, J Li, Z Chang, H Wang - Environmental Science and Pollution …, 2022 - Springer
The groundwater contamination source identification (GCSI) can provide important bases for
the design of pollution remediation plans. The Bayesian theory is commonly used in the …
the design of pollution remediation plans. The Bayesian theory is commonly used in the …