解决水分系统泄漏检测数据的局限性:创建数据,减少数据需求和知识转移
Yipeng Wu1, Shuming Liu2, Zoran Kapelan3
1School of Environment, Tsinghua University, 100084, Beijing, China; Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, the Netherlands.
Water research
|September 21, 2024
概括
水分系统面临严重的泄漏问题,浪费资源和能源. 本综述对数据驱动的泄漏检测方法进行了分类,并强调了克服数据限制的策略,并建议了未来的研究方向.
科学领域:
- 环境工程 环境工程
- 数据科学数据科学数据科学
- 水资源管理 水资源管理
背景情况:
- 全球各地的水分系统都存在大量的泄漏,造成水的浪费,质量受损,能源消耗增加.
- 有效的泄漏检测对于最小化泄漏时间和减轻这些负面影响至关重要.
- 数据驱动的方法对泄漏检测有希望,但受到有限和昂贵的标签数据的阻碍.
研究的目的:
- 综合审查水分系统泄漏检测的数据驱动方法.
- 根据数据利用,对这些方法进行分类:无监督异常检测,半监督异常检测和监督分类.
- 确定解决数据局限性的策略,并建议未来的研究方向.
主要方法:
- 对数据驱动泄漏检测相关期刊论文的系统审查.
- 基于他们对数据使用的方法 (无监督,半监督,监督) 的方法分类.
- 分析数据创建,减少数据需求和知识转移的策略,以克服数据稀缺.
主要成果:
- 数据驱动的泄漏检测方法根据数据利用被分为三个主要类别.
- 减轻数据限制的策略包括数据创建,减少模型数据需求和知识转移.
- 确定了研究缺口和未来方向,例如数据增强和半监督学习.
结论:
- 解决数据局限性是推动水分系统数据驱动泄漏检测的关键.
- 未来的研究应该集中在数据增强,半监督和多分类方法以及新型知识传输技术上.
- 开发可靠和数据效率高的方法对于实际应用和改善水资源管理至关重要.
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