AI Medical Compendium Journal:
Environmental research

Showing 11 to 20 of 109 articles

The reanalysis of a new strategy for groundwater level prediction using combined simulation of machine learning and Muskingum methods under ecological water replenishment.

Environmental research
Due to its multi-functionality, ecological water replenishment (EWR) has been an important measure for restoring aquifers. However, suitable prediction methods need to be selected for the unique fluctuation exhibited by groundwater level (GWL) in the...

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

Environmental research
To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular sludge (AGS) system, a systematic evaluation of the carbon and nitrogen metabolism process for AGS under different stage is essential. Herein, this study...

Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning.

Environmental research
Microplastics (MPs) are ubiquitous and have various characteristics. However, their impacts on bacterial community functions in lakes remain elusive. In this study, we identified 33 different MPs features including their abundance, shape, color, size...

Classification and regression machine learning models for predicting mixed toxicity of carbamazepine and its transformation products.

Environmental research
Carbamazepine (CBZ) and its transformation products (TPs) often occur in aquatic environments in the form of mixtures, posing potential risks to ecosystems. However, establishing standardized protocols for synthesizing, isolating, and acquiring these...

XIS-PM: A daily spatiotemporal machine-learning model for PM in the contiguous United States.

Environmental research
Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a ...

XIS-temperature: A daily spatiotemporal machine-learning model for air temperature in the contiguous United States.

Environmental research
The challenge of reconstructing air temperature for environmental applications is to accurately estimate past exposures even where monitoring is sparse. We present XGBoost-IDW Synthesis for air temperature (XIS-Temperature), a high-resolution machine...

AI-driven identification of a novel malate structure from recycled lithium-ion batteries.

Environmental research
The integration of Artificial Intelligence (AI) into the discovery of new materials offers significant potential for advancing sustainable technologies. This paper presents a novel approach leveraging AI-driven methodologies to identify a new malate ...

Recent advances in groundwater pollution research using machine learning from 2000 to 2023: A bibliometric analysis.

Environmental research
Groundwater pollution has become a global challenge, posing significant threats to human health and ecological environments. Machine learning, with its superior ability to capture non-linear relationships in data, has shown significant potential in a...

Optimizing carbon source addition to control surplus sludge yield via machine learning-based interpretable ensemble model.

Environmental research
Appropriate carbon source addition can save operational costs and reduce surplus sludge yield in the wastewater treatment plant (WWTP). However, the link between carbon source and surplus sludge yield remains neglected although machine learning (ML) ...

Predicting the adsorption of ammonia nitrogen by biochar in water bodies using machine learning strategies: Model optimization and analysis of key characteristic variables.

Environmental research
Biochar adsorption technology has been widely used to remove ammonia nitrogen from water bodies. However, existing methods for predicting adsorption efficiency often lack sufficient accuracy and practical usability. This study evaluated eight machine...