[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
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 …
New-generation machine learning models as prediction tools for modeling interfacial tension of hydrogen-brine system
Abstract Recently, hydrogen (H 2) gas has gained prodigious attention as a sustainable
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …
Integrating active and passive remote sensing data for mapping soil salinity using machine learning and feature selection approaches in arid regions
SA Mohamed, MM Metwaly, MR Metwalli… - Remote Sensing, 2023 - mdpi.com
The prevention of soil salinization and managing agricultural irrigation depend greatly on
accurately estimating soil salinity. Although the long-standing laboratory method of …
accurately estimating soil salinity. Although the long-standing laboratory method of …
Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm
This study proposes different standalone models viz: Elman neural network (ENN), Boosted
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Global soil salinity prediction by open soil Vis-NIR spectral library
Soil salinization is one of the major degradation processes threatening food security and
sustainable development. Detailed soil salinity information is increasingly needed to tackle …
sustainable development. Detailed soil salinity information is increasingly needed to tackle …
Neurocomputing modelling of hydrochemical and physical properties of groundwater coupled with spatial clustering, GIS, and statistical techniques
Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide.
Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity …
Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity …
Using machine learning algorithms based on GF-6 and Google Earth engine to predict and map the spatial distribution of soil organic matter content
Z Ye, Z Sheng, X Liu, Y Ma, R Wang, S Ding, M Liu, Z Li… - Sustainability, 2021 - mdpi.com
The prediction of soil organic matter is important for measuring the soil's environmental
quality and the degree of degradation. In this study, we combined China's GF-6 remote …
quality and the degree of degradation. In this study, we combined China's GF-6 remote …
Mapping Multi-Depth Soil Salinity Using Remote Sensing-Enabled Machine Learning in the Yellow River Delta, China
H Zhang, X Fu, Y Zhang, Z Qi, H Zhang, Z Xu - Remote Sensing, 2023 - mdpi.com
Soil salinization is a crucial type in the degradation of coastal land, but its spatial distribution
and drivers have not been sufficiently explored especially at the depth scale owing to its …
and drivers have not been sufficiently explored especially at the depth scale owing to its …
Feasibility of computational intelligent techniques for the estimation of spring constant at joint of structural glass plates: a dome-shaped glass panel structure
While serving as a core modelling strategy for explaining physical processes, classical and
physics-based modelling is nevertheless associated with weaknesses such as …
physics-based modelling is nevertheless associated with weaknesses such as …
Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization
The rising heavy metal (HM) pollution in coastal aquifers in rapidly urbanizing areas such as
Dammam leads to significant risks to public health and environmental sustainability …
Dammam leads to significant risks to public health and environmental sustainability …