Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater

SK Bhagat, KE Pilario, OE Babalola, T Tiyasha… - Journal of Cleaner …, 2023 - Elsevier
A wide range of dyes are being disposed in water bodies from several industrial runoff and
the quantity is rapidly increasing over the years. From an environmental safety point of view …

Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …

H Tao, SI Abba, AM Al-Areeq, F Tangang… - … Applications of Artificial …, 2024 - Elsevier
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

Short-term streamflow forecasting using hybrid deep learning model based on grey wolf algorithm for hydrological time series

HC Kilinc, A Yurtsever - Sustainability, 2022 - mdpi.com
The effects of develo** technology and rapid population growth on the environment have
been expanding gradually. Particularly, the growth in water consumption has revealed the …

Application of novel artificial bee colony optimized ANN and data preprocessing techniques for monthly streamflow estimation

OM Katipoğlu, M Keblouti, B Mohammadi - Environmental Science and …, 2023 - Springer
Streamflow estimation is important in hydrology, especially in drought and flood-prone
areas. Accurate estimation of streamflow values is crucial for the sustainable management of …

AI and machine learning for soil analysis: an assessment of sustainable agricultural practices

M Awais, SMZA Naqvi, H Zhang, L Li, W Zhang… - Bioresources and …, 2023 - Springer
Sustainable agricultural practices help to manage and use natural resources efficiently. Due
to global climate and geospatial land design, soil texture, soil–water content (SWC), and …

Sustainable irrigation requirement prediction using Internet of Things and transfer learning

A Blessy, A Kumar, AQ Md, AI Alharbi, A Almusharraf… - Sustainability, 2023 - mdpi.com
Irrigation systems are a crucial research area because it is essential to conserve fresh water
and utilize it wisely. As a part of this study, the reliability of predicting the usage of water in …

Research on robust inversion model of soil moisture content based on GF-1 satellite remote sensing

L Luo, Y Li, F Guo, Z Huang, S Wang, Q Zhang… - … and Electronics in …, 2023 - Elsevier
This study aims to improve the accuracy and applicability of traditional linear regression and
machine learning algorithms for monitoring soil moisture content by satellite remote sensing …

[HTML][HTML] Inversion of large-scale citrus soil moisture using multi-temporal Sentinel-1 and Landsat-8 data

Z Wu, N Cui, W Zhang, D Gong, C Liu, Q Liu… - Agricultural Water …, 2024 - Elsevier
Soil moisture is a significant variable in agricultural study and precision irrigation decision-
making. It determines the soil water availability for plants, directly influencing plant growth …

Data mining predictive algorithms for estimating soil water content

S Emami, V Rezaverdinejad, H Dehghanisanij… - Soft Computing, 2024 - Springer
Soil water content (SWC) plays a key role in the management of water and soil resources.
Accurate prediction of SWC is an important issue in water and soil studies. Recently, some …

A new hybrid approach to assessing soil quality using neutrosophic fuzzy-AHP and support vector machine algorithm in sub-humid ecosystem

B Özkan, O Dengiz, P Alaboz, NS Kaya - Journal of Mountain Science, 2023 - Springer
Soil quality determination and estimation is an important issue not only for terrestrial
ecosystems but also for sustainable management of soils. In this study, soil quality was …