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Updated: Jun 5, 2025

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation
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将机器学习算法与下水道过程模型集成,实现快速预测和实时控制下水道系统中的H2S污染

Zhensheng Liang1,2, Wenlang Xie1,2, Hao Li1,2

  • 1School of Environmental Science & Engineering, Guangdong Provincial Key Lab of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou, 510275, China.

Water research X
|December 13, 2024
PubMed
概括

一个新的快速预测模型 (SPM) 将下水道过程建模与机器学习相结合,用于快速检测硫化 (H2S). 这种方法可以实现实时控制,提高安全性并减少下水道系统中化学品的使用.

关键词:
机器学习算法 机器学习算法实时控制 实时控制下水道中的硫化物污染.斯威夫特预测模型的模型已验证的动态下水道过程模型.

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