This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

Globally, wastewater management is a major issue. Using AI has improved treatment facility
design and efficacy. AI techniques for wastewater treatment, such as pollutant identification …

Water-quality monitoring in urban lakes is of paramount importance due to the direct
implications for ecosystem health and human well-being. This study presents a novel …

Rivers play an essential role in supplying high-quality water to diverse sectors.
Understanding water quality indicators and systematic monitoring is crucial for water …

Increases in population and prosperity are linked to a worldwide rise in garbage. The
“classification” and “recycling” of solid waste is a crucial tactic for dealing with the waste …

This study examines the importance of natural resource diversification for China's green
economic revival using the data from 1990 to 2021. The study makes use of a massive …

Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO),
are crucial for understanding and assessing the health of aquatic ecosystems. Precise …

The oil and gas industry is known for its rapid technological advancements and the
complexity of its operations, increasingly relying on data-intensive management. As subsea …

About 6.6 million people die every year from air pollution diseases globally. Transportation
industry is considered one of the leading contributors in air pollution. This research utilizes …

Electrochemical is a promising approach for the removal of ammonia nitrogen, but the
challenge is to achieve better performance under lower energy consumption. In this study, a …