Liu Bo-Qi1, Zhou Ding-Jie2, Zhao Yang1

  • 1State Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian, China.

PloS one
|June 10, 2025
PubMed
概括

XGBoost和Support Vector Machine (SVR) 模型对预测废水废水质量的预测非常有希望. XGBoost为优化废水处理厂运营和环境可持续性提供了最佳的准确性和稳定性.