关键词: 时间序列, 分段线性表示, 二叉树层次遍历, 符号化, 自底向上

Abstract: Current piecewise linear representation methods just use heuristics method to extract the local feature points as the piecewise points. It usually falls into local optimization and cannot represent the global feature of the series very well. Besides, it usually uses the fitting error as the single threshold that cannot accurately predict the number of the sections. These methods cannot meet the application of time series analysis in late. This paper proposes a new representation method—PLR_BTBU which is based on the fixed section number method. The proposed method firstly uses the binary tree-traversal level method to divide the series into rough segments. Then, it uses the slope change characteristics to symbol the whole series. After that, the symbolic feature segments are initially used to determine the distribution of the piecewise points in each initial segment. Finally, an improved BU algorithm is used to fuse each sub sequence to the segment number. The experimental results show that the proposed method not only can preserve the global feature of time series, but also can get a smaller fitting error between the original time series and the new series compared with other algorithms.

Key words: time series, piecewise linear representation, binary tree-traversal level, symbolization, bottom-up