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Using Deep Learning to Optimize the Allocation of Rural Education Resources Under the Background of Rural Revitalization

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  • Xiaojuan Zhao

    (Jiaozuo University, China)

Abstract

Through a large amount of literature research, the current status of rural education resource allocation, the application of deep learning in education resource optimization, and the challenges and solutions faced are sorted out. A rural education resource optimization model based on deep learning is designed, and data collection and analysis, modeling of education resource allocation optimization problems, and optimization algorithm design based on deep learning are elaborated in detail. After experimental evaluation, the optimization algorithm based on deep learning is compared with the traditional optimization method. The results show that the deep learning model has significant advantages in resource allocation accuracy, educational equity, and teaching quality improvement. The research results provide a scientific basis for education decision makers, help the rational allocation and efficient use of rural education resources, and promote the implementation of the rural revitalization strategy.

Suggested Citation

  • Xiaojuan Zhao, 2025. "Using Deep Learning to Optimize the Allocation of Rural Education Resources Under the Background of Rural Revitalization," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 16(1), pages 1-18, January.
  • Handle: RePEc:igg:jaeis0:v:16:y:2025:i:1:p:1-18
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