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在西北城市的废水处理中,用随机森林回归模型预测水质和减少碳的机制
Jingjing Sun1, Xin Guan2, Xiaojun Sun3
1School of Public Administration, Guangzhou University, Guangzhou, 510006, China.
Scientific reports
|December 29, 2024
概括
这项研究开发了一种随机森林回归模型,以准确预测中国西北地区的城市废水质量,帮助水资源管理和减少碳排放.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 数据科学数据科学数据科学
背景情况:
- 中国西北地区城市化加快的速度增加了对有效的城市废水处理和水质管理的需求.
- 水资源压力是该地区的一个重大挑战,需要有效的废水管理和碳减排解决方案.
研究的目的:
- 在中国西北地区探索城市废水处理和碳减排机制.
- 通过在线监测数据分析不同废水处理工艺对关键水质参数的影响.
- 评估水质指标预测模型的应用和性能.
主要方法:
- 利用试点废水处理系统的在线监测数据.
- 开发并应用一个随机森林回归 (RFR) 模型,集成包装集体学习和随机子空间理论.
- 评估了RFR模型在预测化学氧气需求 (COD),氨 (NH4+-N),总 (TP) 和总 (TN) 的性能.
主要成果:
- 对于所有评估的水质指标,RFR模型表现出极好的预测准确性和稳定性.
- 获得了高的R平方值,包括0.99954的COD和0.99989的NH4+-N,TP和TN.
- 在预测所有水质指标方面表现优于其他五种模型.
结论:
- RFR模型为优化废水处理技术提供了一个强大的工具.
- 这些发现支持在中国西北地区制定有效的水资源管理政策.
- 为推进城市废水处理和水资源决策提供理论和实证见解.
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