Artificial neural networks vis-à-vis MODFLOW in the simulation of groundwater: A review
N Zeydalinejad - Modeling Earth Systems and Environment, 2022 - Springer
Although numerical and non-numerical models of groundwater flow and transport have
separately been reviewed in several studies, they have not hitherto been reviewed …
separately been reviewed in several studies, they have not hitherto been reviewed …
Multi-step ahead modelling of river water quality parameters using ensemble artificial intelligence-based approach
In this study, three single Artificial Intelligence (AI) based models ie, Back Propagation
Neural Network (BPNN), Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector …
Neural Network (BPNN), Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector …
Multi-region modeling of daily global solar radiation with artificial intelligence ensemble
Solar radiation data are crucial for the design and evaluation of solar energy systems,
climatic studies, water resources management, estimating crop productivity, etc. As so, for …
climatic studies, water resources management, estimating crop productivity, etc. As so, for …
Metro-environmental data approach for the prediction of chemical oxygen demand in new Nicosia wastewater treatment plant
This study aimed at employing three data-driven models, namely the Hammerstein–Weiner
(HW) model, support vector machine (SVM), and feedforward back propagation neural …
(HW) model, support vector machine (SVM), and feedforward back propagation neural …
Optimization of the groundwater remediation process using a coupled genetic algorithm-finite difference method
In situ chemical oxidation using permanganate as an oxidant is a remediation technique
often used to treat contaminated groundwater. In this paper, groundwater flow with a full …
often used to treat contaminated groundwater. In this paper, groundwater flow with a full …
Use of exploratory fitness landscape metrics to better understand the impact of model structure on the difficulty of calibrating artificial neural network models
Abstract Artificial Neural Network (ANN) models have been used for hydrological and water
resources modelling for several decades, where their calibration (“training”) has received …
resources modelling for several decades, where their calibration (“training”) has received …
Performance comparison of physical process-based and data-driven models: a case study on the Edwards Aquifer, USA
A Zhang, J Winterle, C Yang - Hydrogeology Journal, 2020 - Springer
Physical process-based groundwater flow models are the major tools for studying fluid-flow
behavior and for simulating the hydrological responses of water levels and spring discharge …
behavior and for simulating the hydrological responses of water levels and spring discharge …
Artificial neural network analysis of sulfide production in a Moroccan sewerage network
A El Brahmi, S Abderafi, R Ellaia - Indonesian Journal of Science …, 2021 - ejournal.kjpupi.id
Sulfide in urban wastewater leads to the formation of hydrogen sulfide and its release in the
air. This molecule is an odorous compound, representing an annoyance and health threat …
air. This molecule is an odorous compound, representing an annoyance and health threat …
Estimation of Global Solar Radiation using Back Propagation Neural Network: A case study Tripoli, Libya
N Naser, A Abdelbari - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Adequate information on global solar radiation with relevant meteorological parameters at
any location is necessary for planning, designing, and prediction of the efficiency and …
any location is necessary for planning, designing, and prediction of the efficiency and …
[PDF][PDF] Forecasting of monthly average global solar radiation in Libya
A Shaban - Master of Science, Nicosia, 2019 - docs.neu.edu.tr
Adequate information on global solar radiation with relevant meteorological parameters at
any a location, is necessary for planning, designing, and prediction of the efficiency and …
any a location, is necessary for planning, designing, and prediction of the efficiency and …