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

Shuhui Yu, Ya Yang, Jiamin Li, Keyu Guo, Zeyu Wang and Yuwei Liu ()
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Shuhui Yu: Guangzhou Huashang College
Ya Yang: Anhui Jianzhu University
Jiamin Li: University of Westminster
Keyu Guo: Wuhan University
Zeyu Wang: Guangzhou University
Yuwei Liu: China University of Geosciences

Palgrave Communications, 2024, vol. 11, issue 1, 1-14

Abstract: 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.

Date: 2024
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DOI: 10.1057/s41599-024-02765-4

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