Abstract: This paper presents a new method of fuzzy envelop distance for comparing time series similarity to improve the widely used envelop distance with fuzzifying two clear discriminant boundaries, thus not only reducing the sensitivity of the discriminant results to boundary parameter values, but also making the discriminant method more robust. The new method is then applied to recognize the economic meaning of the macroeconomic independent factors by comparing the similarity between the independent components and economic indicators. And the results, compared with that of the original envelop distance, show that the performance of similarity mining between time series is highly improved.

Key words: time series similarity, envelop distance, fuzzy sets

摘要： 针对广泛应用的时间序列相似性比较方法——包络线距离法因刚性判别边界导致的缺陷，引入模糊集合对该方法中的两个判别边界进行模糊化，减少判别结果对于边界参数值的敏感性，增加了判别方法的稳定性。实验结果表明，改进后方法的判别效果有较大改善，在宏观经济波动源的经济意义识别应用中做了有益尝试。

关键词: 时间序列相似性, 包络线距离法, 模糊集合