A systematic review of machine learning techniques and applications in soil improvement using green materials

AH Saad, H Nahazanan, B Yusuf, SF Toha, A Alnuaim… - Sustainability, 2023 - mdpi.com
According to an extensive evaluation of published studies, there is a shortage of research on
systematic literature reviews related to machine learning prediction techniques and …

Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models

R Barzegar, E Fijani, AA Moghaddam… - Science of the Total …, 2017 - Elsevier
Accurate prediction of groundwater level (GWL) fluctuations can play an important role in
water resources management. The aims of the research are to evaluate the performance of …

A new development of ANFIS–GMDH optimized by PSO to predict pile bearing capacity based on experimental datasets

H Harandizadeh, D Jahed Armaghani… - Engineering with …, 2021 - Springer
Prediction of ultimate pile bearing capacity with the aid of field experimental results through
artificial intelligence (AI) techniques is one of the most significant and complicated problem …

Assessment of scouring around spur dike in cohesive sediment mixtures: A comparative study on three rigorous machine learning models

M Pandey, M Jamei, I Ahmadianfar, M Karbasi… - Journal of …, 2022 - Elsevier
Spur dike has been widely used as one of the river training structures to increase the
stability of riverbanks and embankments. Scour around spur dikes affects their hydraulic …

Groundwater level response identification by hybrid wavelet–machine learning conjunction models using meteorological data

S Samani, M Vadiati, Z Nejatijahromi, B Etebari… - … Science and Pollution …, 2023 - Springer
Due to its heterogeneous and complex nature, groundwater modeling needs great effort to
quantify the aquifer, a crucial tool for policymakers and hydrogeologists to understand the …

[HTML][HTML] GMDH-type neural network approach for modeling the discharge coefficient of rectangular sharp-crested side weirs

I Ebtehaj, H Bonakdari, AH Zaji, H Azimi… - Engineering Science and …, 2015 - Elsevier
Estimating the discharge coefficient using hydraulic and geometrical specifications is one of
the influential factors in predicting the discharge passing over a side weir. Taking into …

Prediction of maximum scour depth near spur dikes in uniform bed sediment using stacked generalization ensemble tree-based frameworks

M Pandey, M Jamei, M Karbasi… - Journal of Irrigation …, 2021 - ascelibrary.org
The scouring process near spur dikes could jeopardize the stability of riverbanks. Thus,
accurate estimation of the maximum scour depth near spur dikes is crucial in river …

NF-GMDH-Based self-organized systems to predict bridge pier scour depth under debris flow effects

M Najafzadeh, F Saberi-Movahed… - Marine Georesources …, 2018 - Taylor & Francis
Existence of debris structures inevitably ascends the rate of scour process around bridge
piers and flow area not only lead into remarkable deviation of flow but also increase the …

Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design

S Shaghaghi, H Bonakdari, A Gholami, I Ebtehaj… - Applied Mathematics …, 2017 - Elsevier
Predicting the behavior and geometry of channels and alluvial rivers in which erosion and
sediment transport are in equilibrium is among the most important topics relating to river …

Evaluation of neuro-fuzzy GMDH-based particle swarm optimization to predict longitudinal dispersion coefficient in rivers

M Najafzadeh, A Tafarojnoruz - Environmental Earth Sciences, 2016 - Springer
In the present research, neuro-fuzzy-based group method of data handling (NF-GMDH) has
been applied to evaluate the longitudinal dispersion coefficient in rivers. The NF-GMDH …