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Evaluation scheme design of college information construction based on a combined algorithm.

Caiyou Shen1, Yingjuan Shi1, Jing Fang2

  • 1Institute of Cyberspace Security, Jinhua Advanced Research Institute, Jinhua, Zhejiang, China.

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|June 22, 2023
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Summary

This study introduces a novel evaluation method for University Information Construction (UIC) using the Analytical Hierarchy Process (AHP) and Particle Swarm Optimization-based back-Propagation Neural Network (PSO-BPNN). The developed model accurately assesses UIC effectiveness, aiding university administration and decision-making.

Keywords:
AHPInformatization constructionPSO-BP

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Area of Science:

  • Educational Technology
  • Computer Science
  • Information Management

Background:

  • Evaluating the impact of informatization construction (IC) is crucial for university administration and decision-making.
  • Existing methods for assessing education informatization (EI) face challenges with grade evaluation fuzziness.
  • University Information Construction (UIC) requires robust evaluation frameworks to guide development.

Purpose of the Study:

  • To develop an advanced evaluation method for University Information Construction (UIC).
  • To address the fuzziness inherent in evaluating the effectiveness of informatization construction (IC).
  • To provide a data-driven approach for university administration and strategic decision-making.

Main Methods:

  • Constructed a data-driven evaluation index system for UIC with 16 second-class and 4 first-class indicators (infrastructure, resource management, information management, safeguard measures).
  • Applied the Analytical Hierarchy Process (AHP) to determine the weights of the first-class indicators within the IC model.
  • Utilized the Particle Swarm Optimization-based back-Propagation Neural Network (PSO-BPNN) algorithm, optimizing inertia weight and learning factors, for fitting and analyzing UIC levels.

Main Results:

  • The proposed PSO-BPNN model demonstrated superior training impact compared to traditional methods.
  • The evaluation method accurately reflects the effectiveness of University Information Construction (UIC).
  • The integrated AHP and PSO-BPNN approach effectively mitigates fuzziness in grade evaluation for IC.

Conclusions:

  • The developed AHP-PSO-BPNN model offers a precise and reliable method for evaluating UIC.
  • This approach enhances the accuracy of assessing informatization construction (IC) and its impact on education informatization (EI).
  • The findings support improved university administration and informed decision-making in higher education technology development.