1. Engineering Institute of Corps of Engineers, PLA University of Science and Technology, Nanjing Jiangsu 210007,China 2. The first Detachment of CAPF Hainan Province Corps, Haikou Hainan 570000,China
Abstract:Most of the existing similarity measurement, based on Euclidean distance, cannot be applied directly and effectively to similarity matching of the timeseries with different granularities. This paper proposed a new similarity measure based on the sample of the corresponding D-value. It firstly expounded the definition of the time-series with different granularities, and defined the sample of the corresponding D-value; secondly it put forward the similarity matching algorithm; finally, the experimental results prove that the algorithm can effectively measure the similarity of time-series with multiple granularities.
邵校莎莎 郝文宁 靳大卫 王莹. 不同粒度时间序列相似性度量[J]. 计算机应用, 2011, 31(12): 3285-3287.
SHAO Xiao-shasha HAO Wen-ning JIN Da-wei WANG Ying. Similarity measurement of time-series data with different granularities. Journal of Computer Applications, 2011, 31(12): 3285-3287.