Chinese Journal of Computers   Full Text
Title	The Symbolic Algorithm for Time Series Data Based on Statistic Feature
Authors	ZHONG Qing-Liu CAI Zi-Xing
Address	(Center of Intelligent System and Software, School of Information Science and Engineering,　　Central South University, Changsha 410083)
Year	2008
Issue	No.10(1857—1864)
Abstract &   Background	Abstract A new symbolic algorithm for Time Series Data Based on Statistic Feature is put forward in order to surmount the bugs with which SAX (Symbolic Aggregate Approximation) Algorithm can not describe time series information fully. This algorithm, differing from the SAX, considered the symbolic as vector, and Mean and variance from each subsequence were regarded as components by which its mean value and radiation degree are described respectively. Since it could provide more information described time series than SAX do, more accuracy result could be get when it is applied to time series data-mining. Its excellent behave. have been proved by a lot of experiments. Keywords time series analysis; symbolic representation; symbolic aggregate approximation(SAX) Background This research is supported by National Project for basal Research of P.R. China(A1420060159). Research on the Theory, Model and Method of mobile cooperate technology. The research group has been working on many aspects of the Project since 2006,have published many papers.In this paper, authors discuss a new model of time series calculation for detecting mobile action.This model is helpful to improve the performance in detection.