[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
H Tao, MM Hameed, HA Marhoon… - Neurocomputing, 2022 - Elsevier
Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …
essential for enhancing the planning and management of water resources. Over the past two …
Recent advances and applications of surrogate models for finite element method computations: a review
J Kudela, R Matousek - Soft Computing, 2022 - Springer
The utilization of surrogate models to approximate complex systems has recently gained
increased popularity. Because of their capability to deal with black-box problems and lower …
increased popularity. Because of their capability to deal with black-box problems and lower …
Gaussian process regression tuned by bayesian optimization for seawater intrusion prediction
G Kopsiaftis, E Protopapadakis… - Computational …, 2019 - Wiley Online Library
Accurate prediction of the seawater intrusion extent is necessary for many applications, such
as groundwater management or protection of coastal aquifers from water quality …
as groundwater management or protection of coastal aquifers from water quality …
Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm
Groundwater resources constitute the main source of clean fresh water for domestic use and
it is essential for food production in the agricultural sector. Groundwater has a vital role for …
it is essential for food production in the agricultural sector. Groundwater has a vital role for …
The importance of uncertainty quantification in model reproducibility
V Volodina, P Challenor - Philosophical Transactions of …, 2021 - royalsocietypublishing.org
Many computer models possess high-dimensional input spaces and substantial
computational time to produce a single model evaluation. Although such models are often …
computational time to produce a single model evaluation. Although such models are often …
Uncertainty-based simulation-optimization using Gaussian process emulation: application to coastal groundwater management
MM Rajabi, H Ketabchi - Journal of hydrology, 2017 - Elsevier
Combined simulation-optimization (S/O) schemes have long been recognized as a valuable
tool in coastal groundwater management (CGM). However, previous applications have …
tool in coastal groundwater management (CGM). However, previous applications have …
SAV decoupled ensemble algorithms for fast computation of Stokes–Darcy flow ensembles
Numerical modeling and simulation of complex systems is often subject to uncertainties in
model parameters. Many popular uncertainty quantification (UQ) methods require repeated …
model parameters. Many popular uncertainty quantification (UQ) methods require repeated …
Faster than real time tsunami warning with associated hazard uncertainties
Tsunamis are unpredictable events and catastrophic in their potential for destruction of
human lives and economy. The unpredictability of their occurrence poses a challenge to the …
human lives and economy. The unpredictability of their occurrence poses a challenge to the …
Transfer prior knowledge from surrogate modelling: A meta-learning approach
Surrogate modelling has emerged as a useful technique to study complex physical and
engineering systems in various disciplines, especially for engineering analysis. Previous …
engineering systems in various disciplines, especially for engineering analysis. Previous …
Stochastic nonlinear model predictive control using Gaussian processes
E Bradford, L Imsland - 2018 european control conference …, 2018 - ieeexplore.ieee.org
Model predictive control is a popular control approach for multivariable systems with
important process constraints. The presence of significant stochastic uncertainties can …
important process constraints. The presence of significant stochastic uncertainties can …