Prediction of Chinese energy structure based on Convolutional Neural Network‐Long Short‐Term Memory (CNN‐LSTM)-Reference-Cited by-同舟云学术

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Prediction of Chinese energy structure based on Convolutional Neural Network‐Long Short‐Term Memory (CNN‐LSTM)

Published:2020-04-15 Issue:8 Volume:8 Page:2680-2689
ISSN:2050-0505
Container-title:Energy Science & Engineering
language:en
Short-container-title:Energy Sci Eng

Author:

Li Yan¹^ORCID,He Yaoyu²,Zhang Meizhen³

Affiliation:

1. College of Economics and Management Taiyuan University of Technology Taiyuan China

2. School of Economics and Management Taiyuan University of Technology Taiyuan China

3. College of Physical Education Taiyuan University of Technology Taiyuan China

Funder

China Scholarship Council

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.698

Reference32 articles.

1. China's post-coal growth

2. China’s coal mine methane regulations have not curbed growing emissions

3. Geoeconomics with Chinese characteristics: the BRI and China’s evolving grand strategy

4. Decline in China's coal consumption: An evidence of peak coal or a temporary blip?

5. Energy structure, marginal efficiency and substitution rate: An empirical study of China

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