Time Series Similarity Search Algorithm Based on Bending Degree of Angular Point

Aiming at the lack of similar sub-patterns discovery algorithm from time series based on points distance such as poor robustness,an algorithm is proposed for similarity measure and approximate representation of time series based on morphological character.Fully used the time-varying characteristics,time series are divided by angular points,and its characters are extracted with bending degrees at angular points to approximate the time series.The algorithm does not depend on the length of time series and domain knowledge.Experimental results show that this algorithm is not only invariant to translation and scalability,but has good robustness,and the results are more effective.