The existing method of determining the size of the time series sliding window by empirical value exists some problems which should be solved urgently, such as when considering a large amount of information and high density of the original measurement data collected from industry equipment, the important information of the data cannot be maximally retained, and the calculation complexity is high. Therefore, by studying the effect of sliding window on time series similarity technology in practical application, an algorithm to determine the initial size of the sliding window is proposed. The upper and lower boundary curves with a higher fitting degree are constructed, and the trend weighting is introduced into the $ LB\_Hust $ distance calculation method to reduce the difficulty of mathematical modeling and improve the efficiency of data similarity computation.

中文翻译：

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基于优化滑动窗口尺寸的时间序列相似度计算的双向加权边界距离算法

现有的根据经验值确定时间序列滑动窗口大小的方法存在一些亟待解决的问题，例如当考虑大量信息和从工业设备收集的原始测量数据的高密度时，重要信息不能最大程度地保留数据的一部分，并且计算复杂度很高。因此，通过在实际应用中研究滑动窗口对时间序列相似度技术的影响，提出了确定滑动窗口初始大小的算法。构造拟合度较高的上下边界曲线，