[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 …

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 …

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 …

Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm

DT Bui, K Khosravi, M Karimi, G Busico… - Science of the Total …, 2020 - Elsevier
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 …

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 …

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 …

SAV decoupled ensemble algorithms for fast computation of Stokes–Darcy flow ensembles

N Jiang, H Yang - Computer Methods in Applied Mechanics and …, 2021 - Elsevier
Numerical modeling and simulation of complex systems is often subject to uncertainties in
model parameters. Many popular uncertainty quantification (UQ) methods require repeated …

Faster than real time tsunami warning with associated hazard uncertainties

D Giles, D Gopinathan, S Guillas, F Dias - Frontiers in Earth Science, 2021 - frontiersin.org
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 …

Transfer prior knowledge from surrogate modelling: A meta-learning approach

M Cheng, C Dang, DM Frangopol, M Beer… - Computers & …, 2022 - Elsevier
Surrogate modelling has emerged as a useful technique to study complex physical and
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 …