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.

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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

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article

Research on Machine Learning-Based Carbon Profiling Algorithm for Enterprises and Production Lines

Shengwei Tang, Xinyue Zhu, Yu Tang, Bochuan Gu et al.
Web Data Mining and Analysis
article

Research on Machine Learning-Based Carbon Profiling Algorithm for Enterprises and Production Lines

Shengwei Tang, Xinyue Zhu, Yu Tang, Bochuan Gu, Mengdi Zeng
article en

Abstract

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.

China Southern Power Grid (China) (CN)
China Southern Power Grid
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Web Data Mining and Analysis
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