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.
2011, Vol. 31 
