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Related Experiment Video

Updated: Aug 30, 2025

Deep Neural Networks for Image-Based Dietary Assessment
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Green Finance Evaluation Based on Neural Network Model.

Ke Wang1

  • 1School of Economics and Management, Huzhou College, Huzhou, Zhejiang 313000, China.

Computational Intelligence and Neuroscience
|August 29, 2022
PubMed
Summary
This summary is machine-generated.

This study develops a green finance evaluation system using the Analytic Hierarchy Process (AHP). Urban green finance growth is linked to environmental businesses, capital efficiency, and government support.

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Area of Science:

  • Environmental Economics
  • Urban Planning
  • Financial Systems

Background:

  • Green finance is crucial for sustainable urban development.
  • Existing evaluation systems may lack comprehensiveness.
  • Understanding drivers of urban green finance is essential.

Purpose of the Study:

  • To establish a robust evaluation system for urban green finance.
  • To identify key indicators influencing green finance growth.
  • To provide actionable recommendations for policy and practice.

Main Methods:

  • Utilized the Analytic Hierarchy Process (AHP) to determine indicator weights.
  • Constructed a hierarchical evaluation index system.
  • Analyzed scoring outcomes and changes across multiple cities.

Main Results:

  • Urban green finance growth strongly correlates with environmental protection business development.
  • Efficient capital allocation and governmental/social capital support are significant drivers.
  • Consumption regulation also demonstrates a notable impact on green finance.

Conclusions:

  • The proposed AHP-based system offers a more thorough and reasonable evaluation framework.
  • Key factors for fostering urban green finance include environmental industry growth, capital efficiency, and supportive policies.
  • Targeted interventions in these areas can accelerate sustainable urban financial development.