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Machine learning in environmental research: common pitfalls and best practices
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …
sets and decipher complex relationships between system variables. However, due to the …
Application of machine learning in groundwater quality modeling-A comprehensive review
Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …
prediction of groundwater pollution due to various chemical components is vital for planning …
Drinking water nitrate and human health: an updated review
Nitrate levels in our water resources have increased in many areas of the world largely due
to applications of inorganic fertilizer and animal manure in agricultural areas. The regulatory …
to applications of inorganic fertilizer and animal manure in agricultural areas. The regulatory …
Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach
In recent years, financial institutions (FIs) have tentatively utilized supply chain finance (SCF)
as a means of solving the financing issues of small and medium-sized enterprises (SMEs) …
as a means of solving the financing issues of small and medium-sized enterprises (SMEs) …
[HTML][HTML] Machine learning predictions of nitrate in groundwater used for drinking supply in the conterminous United States
Groundwater is an important source of drinking water supplies in the conterminous United
State (CONUS), and presence of high nitrate concentrations may limit usability of …
State (CONUS), and presence of high nitrate concentrations may limit usability of …
Global isotope hydrogeology―review
Abstract Groundwater 18O/16O, 2H/1H, 13C/12C, 3H, and 14C data can help quantify
molecular movements and chemical reactions governing groundwater recharge, quality …
molecular movements and chemical reactions governing groundwater recharge, quality …
Large scale prediction of groundwater nitrate concentrations from spatial data using machine learning
Reducing nitrogen inputs, in particular nitrate, to groundwater is becoming increasingly
important to fulfil requirements of the European Water Framework Directive. When …
important to fulfil requirements of the European Water Framework Directive. When …
Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods
Although estimating the uncertainty of models used for modelling nitrate contamination of
groundwater is essential in groundwater management, it has been generally ignored. This …
groundwater is essential in groundwater management, it has been generally ignored. This …
[HTML][HTML] Evaluating the predictive power of different machine learning algorithms for groundwater salinity prediction of multi-layer coastal aquifers in the Mekong Delta …
Groundwater salinization is considered as a major environmental problem in worldwide
coastal areas, influencing ecosystems and human health. However, an accurate prediction …
coastal areas, influencing ecosystems and human health. However, an accurate prediction …
An ensemble machine learning approach for forecasting credit risk of agricultural SMEs' investments in agriculture 4.0 through supply chain finance
Credit risk imposes itself as a significant barrier of agriculture 4.0 investments in the supply
chain finance (SCF) especially for Small and Medium-sized Enterprises. Therefore, it is …
chain finance (SCF) especially for Small and Medium-sized Enterprises. Therefore, it is …