Vector Symbolization Algorithm for Time Series Based on Segmentation Mode
Yujuan Chen · Jisuanji gongcheng · 2011
Aiming at defects of equal-length segmentation of time series in symbolic aggregate approximation algorithm(SAX),a vector symbolic algorithm based on segmentation algorithm for time series(SMSAX) is presented.A triangular threshold method is used to extract features of time series which is sampled randomly.The time series maximum compression ratio is calculated as the time window width to extract segmentation points,and further the Segment Mode(SM) of the time series is found.The partition model is used to segment time series to reduce the dimensionality of them by using vector of mean and volatility of sub-sequences to symbolic them.The algorithm segments time sequences based on characters of them,and eliminates the impact of singular points with the fluctuation rate.Experimental results indicate that SMSAX is able to obtain more accurate results than SAX.