An electricity big data application to reveal the chronological linkages between industries-Reference-Cited by-同舟云学术

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An electricity big data application to reveal the chronological linkages between industries

Published:2024-06-12 Issue: Volume: Page:1-19
ISSN:0953-5314
Container-title:Economic Systems Research
language:en
Short-container-title:Economic Systems Research

Author:

He Kehan¹^ORCID,Coffman D’Maris¹^ORCID,Hou Xingzhe²,Li Jinkai³,Mi Zhifu¹^ORCID

Affiliation:

1. The Bartlett School of Sustainable Construction, University College London, London, UK

2. Electric Power Research Institute, State Grid Chongqing Electric Power Company, Chongqing, People’s Republic of China

3. School of Economics, Beijing Institute of Technology, Beijing, People's Republic of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09535314.2024.2357167

Reference38 articles.

1. Electricity consumption and economic growth: evidence from Pakistan

2. Causality between energy consumption and GDP in the U.S.: evidence from wavelet analysis

3. Disaggregating input–output tables in time: the temporal input–output framework

4. Real-World Evidence, Causal Inference, and Machine Learning

5. Dong X. S. Qian L. J. Huang L. & IEEE. (2017). A CNN based bagging learning approach to short-term load forecasting in smart grid. 2017 IEEE smartworld ubiquitous intelligence & computing advanced & trusted computed scalable computing & communications cloud & big data computing internet of people and smart city innovation (Smartworld/Scalcom/Uic/Atc/Cbdcom/Iop/Sci).

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