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Updated: Jun 27, 2025

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用机器学习方法评估下水道系统的雨水流入和透情况

Yong Wang1, Biao Huang2, David Z Zhu3

  • 1School of Civil and Environmental Engineering, Ningbo University, Ningbo 315211, China.

Water science and technology : a journal of the International Association on Water Pollution Research
|April 28, 2024
PubMed
概括

机器学习模型,包括长期短期记忆 (LSTM),准确预测下水道流和降雨衍生的流入/透 (RDII). 这些模型在大雨期间估计RDII的性能优于传统方法.

关键词:
长期短期记忆 长期短期记忆机器学习是机器学习.降雨产生的流入和透.随机的森林随机的森林下水道流量预测预测

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