In the pursuit of understanding surface water quality for sustainable urban management, we created a machine learning modeling framework that utilized Random Forest (RF), Cubist, Extreme Gradient Boosting (XGB), Multivariate Adaptive Regression Splin...
The urgent need to eliminate Perfluorooctanoic Acid (PFOA) has positioned electrooxidation (EO) as a key solution for pollutant degradation. This study evaluates several machine learning (ML) models, including K-Nearest Neighbors (KNN), Decision Tree...
The emergence of microplastics (MPs) has become a significant focus of environmental pollution, prompting widespread concern regarding its potential toxicity and impact on the environment and organisms. Recent research indicates notable alterations i...
Vanadium (V) contamination posed a significant environmental challenge, while phytoremediation offered a sustainable solution. Phytoremediation performance was often limited by the slow growth cycles of traditional plants. A novel approach to enhanci...
The existence of antibiotics in water sources poses substantial hazards to both the environment and public health. To effectively monitor and combat this problem, accurate predictive models are essential. This research focused on employing machine le...
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...
Optimizing the dosage of coagulant is a time-consuming process, and real-time evaluation of floc settling velocity can quickly predict the coagulation effect and optimize the dosage. This study used a convolutional neural network (CNN) model to analy...
The environmental impacts of artificial intelligence on a global scale remain underexplored. This study utilizes a balanced panel dataset to examine artificial intelligence's complex role in enhancing global green productivity between 2008 and 2019. ...
The short-term risks associated with atmospheric trace gases, particularly carbon monoxide (CO), are critical for ecological security and human health. Traditional statistical methods, which still dominate the assessment of these risks, limit the pot...
Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrati...