使用图形信号采样理论,利用多层次的相关性来归纳供水系统的监测数据,使用图形信号采样理论
Xiao Zhou1, Yacan Man1, Shuming Liu2
1College of Civil Engineering, Hefei University of Technology, Hefei, China.
Water research X
|December 3, 2024
概括
一种新的基于图形的数据计算 (GDI) 方法有效地处理智能供水系统 (WSS) 中缺少的数据. GDI使用图形结构来利用多层次的数据相关性,以实现准确和可靠的归算,即使缺失值高达80%.
科学领域:
- 环境工程 环境工程
- 数据科学数据科学数据科学
- 信号处理 信号处理
背景情况:
- 智能供水系统 (WSS) 由于缺少数据和设备异常而面临挑战.
- 传统的归算方法难以处理复杂的数据关系和有限的历史信息.
研究的目的:
- 开发一种高效准确的方法,用于在WSS中赋值缺失的数据.
- 为了利用WSS数据中的多层次相关性来改进归算.
主要方法:
- 开发了一种新的基于图形的数据推算 (GDI) 方法.
- 利用图形结构来分析WSS数据中的多层相关性.
- 应用图形信号采样算法来提取低频特征以进行归算.
主要成果:
- GDI的表现优于传统的方法,如霍尔特-冬季,支向量回归和门式循环单元.
- 实现高精度和稳定性,即使有高达80%的缺失数据.
- 消除了复杂的功能工程和预培训的需要.
结论:
- GDI为WSS中缺少数据归算提供了一种简化,高效和准确的解决方案.
- 该方法有效地利用数据的连续性和周期性来实现可靠的归算.
- GDI提高了智能供水系统的可靠性.
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