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Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
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基于异常数据分析的李河水质监测和分析系统的设计和实施
Qirong Lu1,2, Jian Zou1,2, Yingya Ye1,2
1College of Information Science and Engineering, Guilin University of Technology, Guilin, China.
PloS one
|March 18, 2024
概括
这项研究引入了一种水质监测系统,可以减少污染和设备需求. 它分析传感器数据进行早期警告,显示温度,pH和TDS等关键指标的稳定性能.
科学领域:
- 环境科学 环境科学
- 分析化学 分析化学
- 数据科学数据科学数据科学
背景情况:
- 传统的水质检测方法 (温度,pH,度,导电性,TDS) 通常涉及多种仪器,并可能导致二次污染.
- 需要一个全面的水质监测和数据分析系统来简化测量和提高准确性.
研究的目的:
- 开发和评估一种新的水质监测和数据分析系统.
- 评估系统在测量关键水质指标方面的准确性和稳定性.
- 分析历史数据以发现趋势,异常值,并为决策提供信息.
主要方法:
- 实时图形显示和分析历史传感器数据 (温度,pH,度,导电性,TDS).
- 应用国家标准验证方法,报告平均测量误差.
- 使用四分位数方法在超过10万条记录中检测异常值.
- 异常值归算方法的比较,包括K-最近邻近算法.
主要成果:
- 该系统显示温度 (0.42%异常值),pH (0.84%异常值) 和TDS (1.24%异常值) 的测量结果相对稳定.
- 度 (3.11%) 和导电性 (2.92%) 的异常值比例较高.
- 与其他六种方法相比,K-最近邻近算法在归纳异常数据方面表现出优势.
结论:
- 开发的水质监测系统为传统方法提供了稳定高效的替代方案.
- 数据分析能力,包括趋势和异常值的检测,支持对设备维护和水质管理的明智决策.
- 该系统通过实时监测和预警功能来加强区域水质监督.
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