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Updated: May 22, 2025

A Sensitive Visual Method for the Detection of Hydrogen Sulfide Producing Bacteria
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使用机器学习模型加强城市下水道系统中硫化控制:通过使用增强算法开发一种新的预测模拟方法.

Duc Viet Nguyen1, Miran Seo2, Yue Chen1

  • 1Center for Green Chemistry and Environmental Biotechnology (GREAT), Ghent University Global Campus, Incheon 21985, Republic of Korea; Department of Green Chemistry and Technology, Ghent University; Centre for Advanced Process Technology for Urban Resource Recovery (CAPTURE), Ghent B9000, Belgium.

Journal of hazardous materials
|March 13, 2025
PubMed
概括

这项研究引入了先进的机器学习,特别是 eXtreme Gradient Boosting (XGBoost),以准确预测下水道系统中硫化的形成. 该模型确定了最大限度地减少这种腐蚀性气体的最佳条件,从而改善了下水道网络管理.

关键词:
提升模型的提升控制战略 控制策略硫化是一种硫化.下水道系统的下水道系统.模拟模拟是为了模拟.

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