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Trend prediction of chaotic time series / 西安交通大学学报·英文版
Academic Journal of Xi&#39 ; an Jiaotong University;(4): 38-41, 2007.
Article in Chinese | WPRIM | ID: wpr-844873
ABSTRACT
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.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Academic Journal of Xi'an Jiaotong University Year: 2007 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Academic Journal of Xi'an Jiaotong University Year: 2007 Type: Article