创新的多步和同步软传感预测COD和NH在WWTP通过多式联络数据和多重注意力机制

Junchen Li1, Sijie Lin2, Liang Zhang3

  • 1School of Environment, Harbin Institute of Technology, Harbin 150090, PR China; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China.

Water research
|March 6, 2025
PubMed
概括

这项研究引入了一种新的AI模型,用于预测废水中的化学氧气需求 (COD) 和氨 (NH3). 泰德-TCN模型提供了准确,经济高效,多步骤的水质监测.