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The high-quality development of China's green energy economy for promotion of digital finance under deep learning technology

Ximeng Li & Qiaomeng Sun

International Journal of Innovation and Sustainable Development2026https://doi.org/10.1504/ijisd.2026.152280article
AJG 1
Weight
0.50

What the paper says

The purpose of this paper is to investigate how digital finance might support the superior growth of China's green energy economy and its regional diversity.In order to systematically uncover the mechanism of digital finance in optimising resource allocation, supporting green technological innovation, and promoting green consumption behaviour, this paper uses theoretical analysis and a deep learning model as its research objects.The findings demonstrate the considerable regional variation in the promotion of digital finance.As a result, this paper examines and validates the mechanism of digital finance in a number of areas, including resource optimisation, technical innovation, and consumer guidance.It also demonstrates the policy support and the regulatory impact of regional economic growth level.This paper contributes to the research in the areas of digital finance and the green energy economy and serves as a reference for maximising regional development policies, reducing regional disparities, and fostering sustainable development.

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https://doi.org/https://doi.org/10.1504/ijisd.2026.152280

Or copy a formatted citation

@article{ximeng2026,
  title        = {{The high-quality development of China's green energy economy for promotion of digital finance under deep learning technology}},
  author       = {Ximeng Li & Qiaomeng Sun},
  journal      = {International Journal of Innovation and Sustainable Development},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijisd.2026.152280},
}

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The high-quality development of China's green energy economy for promotion of digital finance under deep learning technology

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.