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April 12, 2026Journal of Urban Planning and Development

Application of Deep Learning in the Digital Transformation of Urban Planning

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AZAnni Zhang

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Overview

Urban planning demonstrates improved efficiency using deep learning technologies for cultural preservation and connectivity.

Key Points

  • The research aims to explore how deep learning can optimize urban planning processes in historical areas.
  • Utilized an improved DeepLabv3+ model for pixel-level classification of urban functional zones.
  • Applied a graph attention network to analyze spatial relationships among urban elements.
  • Focused on Beijing’s central axis, rich in cultural significance.
  • Achieved over 90% accuracy in classifying urban functional zones.
  • Revealed complex interactions between urban functions and connectivity.
  • Proposed a framework for integrating AI and big data into smart city strategies.

Cite This Study

Anni Zhang (2026) studied this question.

synapsesocial.com/papers/69db37254fe01fead37c51d0https://doi.org/10.1061/jupddm.upeng-5817
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