A Short-Term Carbon Emission Accounting Method for Power Industry Using Electricity Data Based on a Combined Model of CNN and LightGBM

A Short-Term Carbon Emission Accounting Method for Power Industry Using Electricity Data Based on a Combined Model of CNN and LightGBM

The electric power industry plays a pivotal role in carbon emission control. Accurate and real-time accounting of carbon emissions in the power industry is essential for supporting the carbon reduction of the power industry. At present, the measurement of carbon emissions in the power industry relie...

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Bibliographic Details
Main Author: ZENG Jincan, HE Gengsheng, LI Yaowang, DU Ershun, ZHANG Ning, ZHU Haojun
Format: Article
Language:zho
Published: Editorial Office of Journal of Shanghai Jiao Tong University 2025-06-01
Series:Shanghai Jiaotong Daxue xuebao
Subjects:
carbon emission accounting using electricity data
convolutional neural networks (cnns)
light gradient boosting machine (lightgbm)
carbon emissions
machine learning
combined model
Online Access:https://xuebao.sjtu.edu.cn/article/2025/1006-2467/1006-2467-59-6-746.shtml
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