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Traffic Flow Prediction and Application of Smart City Based on Industry 4.0 and Big Data Analysis

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  • Yuqian Gong
  • Man Fai Leung

Abstract

For smart city traffic flow prediction in the period of big data and industry 4.0, the prediction accuracy is low, the prediction is difficult, and the prediction effect is different in different geographical locations. This paper proposes a smart city traffic communication forecast based on Industry 4.0 and big data analysis application. Firstly, this paper theoretically explains the application scenario of urban traffic fault text big data and analyzes the characteristics of related problems, especially the fault problems. Secondly, the AC traffic prediction algorithm is studied, and the application analysis of PVHH, IDT, and Ford–Fulkerson algorithms is applied, respectively. Finally, the above three algorithms are used to predict and analyze traffic flow.

Suggested Citation

  • Yuqian Gong & Man Fai Leung, 2022. "Traffic Flow Prediction and Application of Smart City Based on Industry 4.0 and Big Data Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, August.
    • Handle: RePEc:hin:jnlmpe:5397861
    DOI: 10.1155/2022/5397861
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    Cited by:

    1. Junkai Zhang & Jun Wang & Haoyu Zang & Ning Ma & Martin Skitmore & Ziyi Qu & Greg Skulmoski & Jianli Chen, 2024. "The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends," Sustainability, MDPI, vol. 16(14), pages 1-34, July.

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