Data fusion based phase space reconstruction from multi-time series
发布时间：2025-04-30
点击次数：
- 发布时间：
- 2025-04-30
- 论文名称：
- Data fusion based phase space reconstruction from multi-time series
- 发表刊物：
- International Journal of Database Theory and Application
- 摘要：
- Focused on the problem of imperfect information in the process of reconstruction from single time series, a new technology for phase space reconstruction from multi-time series based on the data fusion is proposed. Firstly, the methods Cao and mutual information are used to select the reconstruction parameters, time delay and embedded dimension; secondly, the social cognitive optimization algorithm is brought to calculate the weights for each variable; thirdly, an adaptive weighted fusion estimating method is applied for data fusion; lastly, the effectiveness of the methods mentioned in this paper is demonstrated by the analysis results of one case study of real chemical plant data sets, and the proposed methods in this paper can improve the completeness of the information of the reconstructed phase space, which is also a good foundation for further analysis of complex system.
- 合写作者：
- <b>Rongxi Wang</b>, Jianmin Gao, Zhiyong Gao, Xu Gao, Hongquan Jiang, and Le Cui
- 卷号：
- 8(6)
- 页面范围：
- 101-110
- 是否译文：
- 否
- 发表时间：
- 2015-12-31