Open Access

Multi-source data-driven technology research on carbon emission dynamics prediction in electric power industry

Ruoyu Wang

Ruoyu Wang

Shenzhen Power Supply Co. LtdShenzhen, China
Search for this author on
Sciendo|Google Scholar
Wang, Ruoyu
, 
Jing Li

Jing Li

Shenzhen Power Supply Co. LtdShenzhen, China
Search for this author on
Sciendo|Google Scholar
Li, Jing
, 
Zhipeng Li

Zhipeng Li

Shenzhen Power Supply Co. LtdShenzhen, China
Search for this author on
Sciendo|Google Scholar
Li, Zhipeng
 and 
Qingchao Sun

Qingchao Sun

Shenzhen Power Supply Co. LtdShenzhen, China
Search for this author on
Sciendo|Google Scholar
Sun, Qingchao
  
Oct 09, 2024
Multi-source data-driven technology research on carbon emission dynamics prediction in electric power industry's Cover Image
About this article
Previous Article
Next Article
Cite
Download Cover
Published Online: Oct 09, 2024
Received: May 30, 2024
Accepted: Sep 05, 2024
DOI: https://doi.org/10.2478/amns-2024-2905
Keywords
© 2024 Ruoyu Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Wang, Ruoyu
Shenzhen Power Supply Co. LtdShenzhen, China
Li, Jing
Shenzhen Power Supply Co. LtdShenzhen, China
Li, Zhipeng
Shenzhen Power Supply Co. LtdShenzhen, China
Sun, Qingchao
Shenzhen Power Supply Co. LtdShenzhen, China
Language:
English
Publication timeframe:
1 times per year
Journal Subjects:
Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
Journal RSS Feed