关键词: 时间序列, 趋势相似性, 模式匹配, 动态时间弯曲（DTW）

Abstract:

In order to further perfect and improve the effect of pattern-based trend similarity measurement of time series, on the basis of piecewise linear representation of time series, this paper realizes the piecewise patterning of time series according to the mean of piecewise subsequence and the derivative sign of its linear fitting function, defines the pattern matching distance by the similarities and differences between patterns, proposes a Dynamic Pattern Matching（DPM） method based on the dynamic programming principle of Dynamic Time Warping（DTW）. The experimental results show that this method can accurately measure the trend similarity of equal-length time series under different compression rates, and the time consumption is low. The unequal length of time series is a manifestation of data missing. The relationship between the measurement effect of this method and the proportion of data missing deserves further study.

Key words: time series, trend similarity, pattern matching, Dynamic Time Warping（DTW）