[HTML][HTML] Machine learning and soil sciences: A review aided by machine learning tools

J Padarian, B Minasny, AB McBratney - Soil, 2020 - soil.copernicus.org
The application of machine learning (ML) techniques in various fields of science has
increased rapidly, especially in the last 10 years. The increasing availability of soil data that …

Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research

SK Bhagat, TM Tung, ZM Yaseen - Journal of Cleaner Production, 2020 - Elsevier
The presence of various forms of heavy metals (HMs)(eg, Cu, Cd, Pb, Zn, Cr, Ni, As, Co, Hg,
Fe, Mn, Sb, and Ce) in water bodies and sediment has been increasing due to industrial and …

Predicting and mapping of soil organic carbon using machine learning algorithms in Northern Iran

M Emadi, R Taghizadeh-Mehrjardi, A Cherati… - Remote Sensing, 2020 - mdpi.com
Estimation of the soil organic carbon (SOC) content is of utmost importance in understanding
the chemical, physical, and biological functions of the soil. This study proposes machine …

Machine learning for predicting greenhouse gas emissions from agricultural soils

A Hamrani, A Akbarzadeh, CA Madramootoo - Science of The Total …, 2020 - Elsevier
Abstract Machine learning (ML) models are increasingly used to study complex
environmental phenomena with high variability in time and space. In this study, the potential …

Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia

SK Bhagat, TM Tung, ZM Yaseen - Journal of Hazardous Materials, 2021 - Elsevier
Lead (Pb) is a primary toxic heavy metal (HM) which present throughout the entire
ecosystem. Some commonly observed challenges in HM (Pb) prediction using artificial …

Efficacy of enzymatically induced calcium carbonate precipitation in the retention of heavy metal ions

AAB Moghal, MA Lateef, SAS Mohammed, K Lemboye… - Sustainability, 2020 - mdpi.com
This study evaluated the efficacy of enzyme induced calcite precipitation (EICP) in restricting
the mobility of heavy metals in soils. EICP is an environmentally friendly method that has …

Prediction of copper ions adsorption by attapulgite adsorbent using tuned-artificial intelligence model

SK Bhagat, K Pyrgaki, SQ Salih, T Tiyasha, U Beyaztas… - Chemosphere, 2021 - Elsevier
Copper (Cu) ion in wastewater is considered as one of the crucial hazardous elements to be
quantified. This research is established to predict copper ions adsorption (Ad) by Attapulgite …

Elaboration, characterization and performance evaluation of a new environmentally friendly adsorbent material based on the reed filter (Typha Latifolia): Kinetic and …

AEL Amri, J Bensalah, Y Essaadaoui, I Lebkiri… - Chemical Data …, 2022 - Elsevier
Heavy metal pollution is a public health problem that should prompt environmental
protection authorities to provide appropriate solutions. The objective of this work concerns …

Experimental design, machine learning approaches for the optimization and modeling of caffeine adsorption

N Taoufik, W Boumya, R Elmoubarki, A Elhalil… - Materials Today …, 2022 - Elsevier
In the current research, the sorption of caffeine on fresh and calcined Cu–Al layered double
hydroxide was comparatively studied based on adsorption parameters, adsorption kinetics …

A field study of nano-FeS loaded lignin hydrogel application for Cd reduction, nutrient enhancement, and microbiological shift in a polluted paddy soil

X Wei, H Chen, D Lin, H Xu, J Wang, J Zhang… - Chemical Engineering …, 2023 - Elsevier
Cadmium (Cd) pollution in paddy soil has caused serious harm to human health. Nano-
ferrous sulfide@ lignin hydrogel (FeS@ LH) composites could be an ideal material for paddy …