An Effective Allocation Model of Computer Teaching Management Resources Based on Particle Swarm Optimization

Authors

  • Xiang Yang Information Construction Management Office, Nanjing University of Finance & Economics

DOI:

https://doi.org/10.3991/ijet.v14i18.11189

Keywords:

computer teaching management, resource allocation model, particle swarm optimization (PSO), educational resources

Abstract


This paper attempts to improve the resource utilization in computer teaching, striking a balance between educational resource and education development. For this purpose, the author systematically investigated the allocation of computer teaching management resources, and set up an effective allocation model of such resources based on particle swarm optimization (PSO). The research results show that the PSO-based model can coordinate the allocation of computer teaching management resources, enhance the utilization rate of teaching resources, and prevent resource waste. With the aid of the proposed model, the imbalance between different counties and districts in the number of computers and teachers was greatly improved, which contributes to the coordinated development of education in the study area. The research findings have great theoretical and social significance for the sustainable development of education and the improvement of the education system.

Author Biography

Xiang Yang, Information Construction Management Office, Nanjing University of Finance & Economics

Xiang Yang, male, was born on March 28, 1982, with a Master's degree,major in Software engineering. He is currently working as an engineer at Nanjing University of Finance and Economics in Nanjing，China. He has been engaged in Network security and information technology in university for more than 10 years. He has published several articles on computer network security and algorithms.

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Published

2019-09-30

How to Cite

Yang, X. (2019). An Effective Allocation Model of Computer Teaching Management Resources Based on Particle Swarm Optimization. International Journal of Emerging Technologies in Learning (iJET), 14(18), pp. 4–15. https://doi.org/10.3991/ijet.v14i18.11189

Issue

Vol. 14 No. 18 (2019)

Section

Papers

License

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