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Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization

Author

Listed:
  • Rui Luan

    (Shenyang Polytechnic College, China)

  • Ping Xu

    (Xihua University, China)

Abstract

In today's society, rural areas face challenges such as complex terrain and uneven population distribution, and infrastructure construction is exceptionally difficult. At the same time, poor information transmission and low communication efficiency have also become a major obstacle to the promotion of the digital economy in rural areas. This study aims to use gradient advancement models to identify potential risks in the growth of the digital economy sector related to rural revitalization. In this study, we used an enhanced hierarchical gradient boosting algorithm. The research results indicate that the introduction of this technology can provide us with a more comprehensive and reliable risk prediction model, thereby more scientifically assisting the development and decision-making of the digital economy in rural areas. This article provides a new perspective and solutions for development issues in rural areas, promoting sustainable development and economic growth in rural areas.

Suggested Citation

  • Rui Luan & Ping Xu, 2024. "Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization," Information Resources Management Journal (IRMJ), IGI Global Scientific Publishing, vol. 37(1), pages 1-21, January.
    • Handle: RePEc:igg:rmj000:v:37:y:2024:i:1:p:1-21
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    References listed on IDEAS

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