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Updated: Jun 17, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

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一个新的合可解释的机器学习框架,用于预测水质和了解水利项目的不同流量排放法规中的环境影响

Xizhi Nong1, Cheng Lai2, Lihua Chen2

  • 1College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China; State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China; Centre for Urban Sustainability and Resilience, Department of Civil, Environmental and Geomatic Engineering, University College London, London WC1E 6BT, UK; School of Computing and Engineering, University of West London, London W5 5RF, UK.

The Science of the total environment
|August 8, 2024
PubMed
概括

本研究引入了一个可解释的机器学习框架,通过分析环境因素和流量排放来预测水质,特别是酸盐指数 (CODMn). 可解释的随机森林模型增强了对复杂水利项目的水质动态的理解.

关键词:
流量排放规则 流量排放规则盆地间的水分转移项目可以解释的机器学习随机森林模型是一个随机森林模型.预测水质水质预测

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