ArticleScientific reports2024
Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Integrating Plant-Based Coagulation and Explainable Machine Learning for Sustainable River Water Treatment.Water environment research : a research publication of the Water Environment Federation · 2026Article
- Development and multi-objective optimization of an automatic filtration system with pressure-based preventive control for efficient irrigation water management.Scientific reports · 2026Article
- Feature-engineered machine learning for daily-scale prediction of effluent total phosphorus and coagulant dosing optimization in full-scale DAF systems.Water science and technology : a journal of the International Association on Water Pollution Research · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
With the accelerated urbanization and economic development in Northwest China, the efficiency of urban wastewater treatment and the importance of water quality management have become increasingly significant. This work aims to explore urban wastewater treatment and carbon reduction mechanisms in Northwest China to alleviate water resource pressure. By utilizing online monitoring data from pilot systems, it conducts an in-depth analysis of the impacts of different wastewater treatment processes on water quality parameters. This work pays particular attention to their impact on key indicators such as Chemical Oxygen Demand (COD), NH
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Registered trials
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