Groundwater level forecasting with machine learning models: A review

KBW Boo, A El-Shafie, F Othman, MMH Khan… - Water Research, 2024 - Elsevier
Groundwater, the world's most abundant source of freshwater, is rapidly depleting in many
regions due to a variety of factors. Accurate forecasting of groundwater level (GWL) is …

Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data

RM Adnan, RR Mostafa, HL Dai… - Engineering …, 2023 - Taylor & Francis
This study investigates the feasibility of a relevance vector machine tuned with improved
Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using …

[HTML][HTML] Compressive strength of concrete containing furnace blast slag; optimized machine learning-based models

M Kioumarsi, H Dabiri, A Kandiri, V Farhangi - Cleaner Engineering and …, 2023 - Elsevier
Abstract Replacing Ordinary Portland Cement (OPC) with industrial waste like Ground
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …

Decomposition integration and error correction method for photovoltaic power forecasting

G Li, X Wei, H Yang - Measurement, 2023 - Elsevier
Photovoltaic power generation has remarkable environmental benefit, and it is one of the
effective means to fundamentally solve environmental problem. An accurate photovoltaic …

Application of artificial intelligence models for prediction of groundwater level fluctuations: Case study (Tehran-Karaj alluvial aquifer)

M Vadiati, Z Rajabi Yami, E Eskandari… - Environmental …, 2022 - Springer
The nonlinear groundwater level fluctuations depend on the interaction of many factors such
as evapotranspiration, precipitation, groundwater abstraction, and hydrogeological …

Water level prediction using various machine learning algorithms: a case study of Durian Tunggal river, Malaysia

AN Ahmed, A Yafouz, AH Birima, O Kisi… - Engineering …, 2022 - Taylor & Francis
ABSTRACT A reliable model to predict the changes in the water levels in a river is crucial for
better planning to mitigate any risk associated with flooding. In this study, six different …

Atmosphere air temperature forecasting using the honey badger optimization algorithm: on the warmest and coldest areas of the world

J Zhou, D Wang, SS Band, E Mirzania… - … of Computational Fluid …, 2023 - Taylor & Francis
Precisely forecasting air temperature as a significant meteorological parameter has a critical
role in environment quality management. Hence, this study employs a hybrid intelligent …

Performance improvement of machine learning models via wavelet theory in estimating monthly river streamflow

K Wang, SS Band, R Ameri, M Biyari, T Hai… - Engineering …, 2022 - Taylor & Francis
River streamflow is an essential hydrological parameters for optimal water resource
management. This study investigates models used to estimate monthly time-series river …

[HTML][HTML] Spatial prediction of groundwater potential and driving factor analysis based on deep learning and geographical detector in an arid endorheic basin

Z Wang, J Wang, J Han - Ecological Indicators, 2022 - Elsevier
Substantial mineral resources are enriched in the arid endorheic basins; however, due to
environmental constraints, these areas face water shortages as well as its extremely uneven …

Estimating equilibrium scour depth around non-circular bridge piers using interpretable hybrid machine learning models

N Eini, S Janizadeh, SM Bateni, C Jun, Y Kim - Ocean Engineering, 2024 - Elsevier
Scouring at bridge piers is a crucial issue that risks bridge collapses, causing economic
losses and endangering public safety. Classic models struggle to accurately estimate …