Energy data temporal information index algorithm based on critical point dynamic adjustment

Zhongli Shen, Qiyue Xie, Fei Jiang and Yi Zuo

International Journal of Global Energy Issues, 2021, vol. 43, issue 5/6, 706-720

Abstract: In order to improve the scheduling ability of temporal information of energy data, an index algorithm of temporal information of energy data based on dynamic adjustment of critical points is proposed. Using the statistical characteristics analysis method, the energy time information structure is analysed with big data. The phase space reconstruction method is used to adjust the structure of the time information of the energy data and reconstruct it adaptively, and extract the relevant characteristics of the time information. Using the method of dynamic adjustment of critical points, the paper studies the attribute clustering and feature retrieval in the process of time information index of energy data. The fuzzy autocorrelation feature matching method is used to realise the time information index of energy data. The simulation results show that this method reduces the index time of energy data and improves the anti-jamming ability of energy data temporal information index.

Keywords: dynamic adjustment; energy data; temporal information; index; feature retrieval. (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=118920 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:43:y:2021:i:5/6:p:706-720

Access Statistics for this article

More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().