Research on Machine Learning-Based Carbon Profiling Algorithm for Enterprises and Production Lines
Carbon profiling technology provides scientific support for carbon emission management at both the enterprise and production line levels. At the enterprise level, it helps identify emission sources, optimize energy use, and assess the effectiveness of green energy, contributing to carbon reduction and brand image enhancement. At the production line level, it focuses on energy and carbon flow analysis, optimizing process flows, and reducing emission intensity. Through data collection, feature extraction, and model building, combined with machine learning algorithms, carbon profiling enables accurate quantification and dynamic adjustment of carbon emissions, supporting enterprises in predicting emission reduction potential and formulating energy-saving strategies. As a crucial tool for achieving carbon neutrality, carbon profiling enhances enterprise energy efficiency, drives green transformation, and provides data support for policy compliance and carbon trading. Its broad application prospects will continue to aid sustainable development.
Authors
- Shengwei Tang
- Xinyue Zhu
- Yu Tang (ORCID: https://orcid.org/0000-0002-0728-0506)
- Bochuan Gu
- Mengdi Zeng
Institutions
- China Southern Power Grid (China) (CN)
Publication Details
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/isneet64164.2024.10956060
- Primary Topic
- Web Data Mining and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- China Southern Power Grid