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Artificial intelligence-enabled smart city construction

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Abstract

This work aims to promote smart city construction and smart city management. Firstly, this work analyzes the relevant theories and processing methods of short-term traffic flow prediction. Secondly, the random forest regression (RFR) theory in machine learning is discussed to realize the short-term traffic flow prediction model (STTPM). Meanwhile, STTPM data are processed by k-nearest neighbors (KNN) and optimized by Complete Ensemble Empirical Mode Decomposition (CEEMD) and RFR method. Finally, the KNN-CEEMD-RFR model is proposed, and the performance of the model is evaluated. The results show that the proposed KNN-CEEMD-RFR model has better traffic prediction effect than support vector regression, RFR model, and CEEMD-RFR model. The prediction of support vector regression model is the worst, followed by RFR model. The mean square error of CEEMD-RFR is about 2% lower than that of RFR without data preprocessing. The mean square error of KNN-CEEMD-RFR model is 4% smaller than that of CEEMD-RFR model. Finally, the prediction accuracy of the proposed KNN-CEEMD-RFR model is more than 92%, which has a very ideal prediction effect. This work provides specific ideas for the application of artificial intelligence in smart city construction and smart city management. The proposed KNN-CEEMD-RFR model for smart city has made an important contribution to the development of traffic management in smart city management.

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Acknowledgements

The authors acknowledge the help from the university colleagues.

Funding

This research received no external funding.

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Authors and Affiliations

  1. School of Civil Engineering, Beijing Jiaotong University, Beijing, 100044, China

    Yanxu Jiang

  2. School of Architecture and Design, Beijing Jiaotong University, Beijing, 100044, China

    Linfei Han

  3. College of Art Design, Shanghai Jian Qiao University, Shanghai, 201306, China

    Yifang Gao

Authors
  1. Yanxu Jiang
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  2. Linfei Han
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  3. Yifang Gao
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Correspondence to Yanxu Jiang or Linfei Han.

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Cite this article

Jiang, Y., Han, L. & Gao, Y. Artificial intelligence-enabled smart city construction. J Supercomput 78, 19501–19521 (2022). https://doi.org/10.1007/s11227-022-04638-6

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  • DOI: https://doi.org/10.1007/s11227-022-04638-6

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