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Exploring low-carbon and sustainable urban transformation design using ChatGPT and artificial bee colony algorithm

Author

Listed:
  • Shuhui Yu

    (Guangzhou Huashang College
    City University of Macau)

  • Ya Yang

    (Anhui Jianzhu University)

  • Jiamin Li

    (University of Westminster)

  • Keyu Guo

    (Wuhan University)

  • Zeyu Wang

    (Guangzhou University)

  • Yuwei Liu

    (China University of Geosciences)

Abstract

The aim of this study is to provide effective solutions to promote the transition of resource-based cities to low carbon and sustainable development. Firstly, this study investigates the background of low-carbon transformation of resource-based cities. Secondly, it introduces the application method of Chat Generative Pre-trained Transformer (ChatGPT) in detail. Finally, this study proposes a comprehensive application of ChatGPT and artificial bee colony (ABC) algorithm. The results show that the average energy utilization efficiency improvement index of the group using ChatGPT is 0.11. The average energy efficiency improvement index of the group using ABC algorithm is 0.02 higher than that of the control group. The integrated application of ChatGPT and ABC algorithm can further improve the low-carbon transformation effect of resource-based cities and achieve the goal of green development.

Suggested Citation

  • Shuhui Yu & Ya Yang & Jiamin Li & Keyu Guo & Zeyu Wang & Yuwei Liu, 2024. "Exploring low-carbon and sustainable urban transformation design using ChatGPT and artificial bee colony algorithm," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02765-4
    DOI: 10.1057/s41599-024-02765-4
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