Modeling and spatio-temporal analysis on CO2 emissions in the Guangdong-Hong Kong-Macao greater bay area and surrounding cities based on neural network and autoencoder-Reference-Cited by-同舟云学术

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Modeling and spatio-temporal analysis on CO2 emissions in the Guangdong-Hong Kong-Macao greater bay area and surrounding cities based on neural network and autoencoder

Published:2024-04 Issue: Volume:103 Page:105254
ISSN:2210-6707
Container-title:Sustainable Cities and Society
language:en
Short-container-title:Sustainable Cities and Society

Author:

Luo Xichun,Liu Chengkun^ORCID,Zhao Honghao^ORCID

Funder

Macau University of Science and Technology

Publisher

Elsevier BV

Reference72 articles.

1. BP, "Statistical review of world energy – all data, 1965-2020.," ed. BP, UK., (2021).

2. Hong Kong annual digest of statistics,2021

3. County-level CO2 emissions and sequestration in China during 1997-2017;Chen;Scientific Data,2020

4. An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration;Chen;Earth System Science Data,2021

5. CNIPA, "China Intellectual Property Statistical Yearbook 2000-2020," 2020 ed. Beijing, 2000-2020.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic spatiotemporal evolution and spatial effect of carbon emissions in urban agglomerations based on nighttime light data;Sustainable Cities and Society;2024-10

2. Effects of 3D urban morphology on CO2 emissions using machine learning: Towards spatially tailored low-carbon strategies in Central Wuhan, China;Urban Climate;2024-09

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