水利信息化Issue(1)：28-35,8.DOI:10.19364/j.1674-9405.2026.01.005
基于滑动窗口采样技术和DTWCorr距离度量的多元时间序列分割方法研究
Research on multivariate time series segmentation method based on sliding window sampling and DTWCorr distance metric
摘要
Abstract
To improve the accuracy of multi-time series event detection in watershed water resource management,in response to the problem that traditional synchronous segmentation methods ignore the time lag and asynchrony between variables,a multi-time series asynchronous segmentation method based on sliding window sampling technology and composite metric(DTWCorr)was proposed.The method first obtained initial segments of each variable using univariate time series segmentation,then integrated multi-variable segment information through time correlation segmentation to capture asynchronous characteristics among variables.Multi-scale sliding windows were subsequently applied to resample the segments,enhancing data robustness.The DTWCorr distance metric was constructed by combining DTW with the Pearson correlation coefficient,and the multi-segment graph shortest path algorithm was used to achieve globally optimal asynchronous segmentation.Experiments based on water quality data from the Taihu Lake watershed demonstrated that this method outperformed traditional synchronous segmentation in segmentation accuracy,inter-variable correlation,and noise robustness.It more accurately reflected the asynchronous variation patterns of multivariate time series.This study provides reliable data support for hydrological event identification and intelligent watershed water resource management.关键词
多元时间序列分割/异步分割/滑动窗口采样/DTWCorr距离/多段图最短路径Key words
multivariate time series segmentation/asynchronous segmentation/sliding window sampling/DTWCorr distance/multi-segment graph shortest path分类
信息技术与安全科学引用本文复制引用
侯开明,岳疆陶,柳飞扬,汪浩航,冯钧..基于滑动窗口采样技术和DTWCorr距离度量的多元时间序列分割方法研究[J].水利信息化,2026,(1):28-35,8.基金项目
国家重点研发计划项目(2024YFC3210800) （2024YFC3210800）
