使用LED光谱仪优化间接废水表征:对回归,缩放和缩小维度方法进行比较分析
Daniel Carreres-Prieto1, Enrique Fernandez-Blanco2, Daniel Rivero2
1Department of Engineering and Applied Techniques, Centro Universitario de la Defensa, Universidad Politécnica de Cartagena, C/ Coronel López Peña S/N, Base Aérea de San Javier, Santiago de La Ribera, 30720, Murcia, Spain. daniel.carreres@cud.upct.es.
Environmental science and pollution research international
|August 28, 2024
概括
通过LED光谱摄影仪,可以通过相关性建模来估计废水污染物负载. 使用数据规范化,PCA和随机森林回归器来预测化学氧气需求和总悬浮固体,实现了最佳性能.
科学领域:
- 环境科学 环境科学
- 分析化学 分析化学
- 水处理技术 水处理技术
背景情况:
- 废水的表征对于有效的处理和环境保护至关重要.
- 间接方法,如LED光谱光度测量,为传统分析提供了成本效益高的替代方案.
- 开发强大的模型对于准确的污染物负载预测至关重要.
研究的目的:
- 评估各种数据处理管道,用于基于LED光谱光度的废水分析.
- 确定预测化学氧气需求 (COD) 和总悬浮固体 (TSS) 的最佳组合技术.
- 加强废水污染物负载的间接表征.
主要方法:
- 在4年内从45个污水处理厂收集了1300个原始和经过处理的废水样本的数据集.
- 测试了84个不同的处理管道,结合了7种回归技术,3种缩放方法和4种缩小维度的方法.
- 使用十倍交叉验证对15个子数据集来评估管道性能.
主要成果:
- 数据规范化之后,主要组件分析 (PCA) 和随机森林回归器显示出卓越的性能.
- 这条管道有效地预测了化学氧气需求 (COD) 和总悬浮固体 (TSS).
- 管道的有效性因回归器类型,缩放,缩小维度和数据特征而异.
结论:
- 数据规范化,PCA和随机森林回归器的组合对于基于LED光谱光度的废水分析非常有效.
- 这种方法显著改善了废水污染物负载的间接表征.
- 强调先进的建模策略在优化废水管理中的重要性.
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