福建师范大学学报（自然科学版）2025，Vol.41Issue(2)：55-64,124,11.DOI:10.12046/j.issn.1000-5277.2024060041
基于变换空间的形态子序列快速提取方法
Fast Extraction Method for Morphological Subsequence Based on Transform Space
摘要
Abstract
Shapelets are the most recognizable subsequence segments in time series data,ca-pable of accurately expressing local morphological features of time series.Existing morphological subsequence extraction methods can effectively reduce the number of morphological subsequences by setting key points,but often ignore the influence of noise and lack optimization for information re-dundancy.To address this issue,this paper proposes an improved method:the time series is smoothed locally using an overlapping sliding window to reduce the influence of noise,and informa-tion redundancy is optimized based on the transformation space.The proposed method can extract morphological subsequences from time series in a low-dimensional space and represent the data.The experimental results show that the new method improves classification efficiency while maintaining classification accuracy.关键词
shapelets/噪声/重叠式滑动窗口/优化/低维空间Key words
shapelets/noise/overlapping sliding window/optimization/low-dimensional space分类
数理科学引用本文复制引用
张癸水,陈黎飞,胡丽莹..基于变换空间的形态子序列快速提取方法[J].福建师范大学学报（自然科学版）,2025,41(2):55-64,124,11.基金项目
国家自然科学基金项目(61672157) （61672157）
