Analysis of Carbon Emission Influencing Factors and Medium- and Long-term Prediction Methods for Mega Cities Based on GDIM and PSO-XGBoost-Reference-Cited by-同舟云学术

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Analysis of Carbon Emission Influencing Factors and Medium- and Long-term Prediction Methods for Mega Cities Based on GDIM and PSO-XGBoost

Published:2023-07-27 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Conference on Power and Energy Technology (ICPET)
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Author:

Chen Tianheng¹,Li Ye¹,Li Shangze²,Qi Bochao³,Li Guodong⁴,Lv Jinbing⁴

Affiliation:

1. State Grid Tianjin Electric Power Company,Tianjin,China,300010

2. Key Laboratory of Smart Grid of Ministry of Education of Tianjin University,Tianjin,China,300072

3. Wuqing District Power Supply Company of State Grid Tianjin Electric Power Company,Tianjin,China,301700

4. State Grid Tianjin Electric Power Company Electric Power Science Research Institute,Tianjin,China,300021

Funder

State Grid Corporation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10367197/10367198/10367671.pdf?arnumber=10367671

Reference6 articles.

1. Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data

2. Towards near real-time, monthly fossil CO2 emissions estimates for the European Union with current-year projections

3. Optimizing Near Real-Time Detection of Deforestation on Tropical Rainforests Using Sentinel-1 Data

4. Satellite-based estimates of decline and rebound in China’s CO 2 emissions during COVID-19 pandemic

5. Near-Real-Time Carbon Emission Accounting Technology Toward Carbon Neutrality

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