Trend prediction of chaotic time series
Li Aiguo;Zhao Cai;Li Zhanhuai
【期刊名称】《西安医科大学学报(英文版)》 【年(卷),期】2007(019)001
【摘要】To predict the trend of chaotic time series in time series analysis and time series data mining fields, a novel predicting algorithm of chaotic time series trend is presented, and an on-line segmenting algorithm is proposed to convert a time series into a binary string according to ascending or descending trend of each subsequence. The on-line segmenting algorithm is independent of the prior knowledge about time series. The naive Bayesian algorithm is then employed to predict the trend of chaotic time series according to the binary string. The experimental results of three chaotic time series demonstrate that the proposed method predicts the ascending or descending trend of chaotic time series with few error. 【总页数】4页(38-41) 【
关
键
词
】
knowledge
acquisition;data
mining;time
series;prediction;chaos
【作者】Li Aiguo;Zhao Cai;Li Zhanhuai
【作者单位】Department of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, China;School of Computer Science and Engineering, Northwestern Polytechnical
Trend prediction of chaotic time series
