Integrated Innovation: Hybrid Optimization Algorithm Drives the Reform of AI Literacy Services in University Libraries

DOI: https://doi.org/10.62517/jbdc.202501222

Author(s)

Zhang Junli1,2,*

Affiliation(s)

1Guilin Tourism College, Guilin Tourism University, Guilin, Guangxi, China 2Guilin Institute of Information Technology, Guilin, Guangxi, China *Corresponding Author.

Abstract

This paper focuses on AI literacy services in university libraries, delving into the issues present in current services and detailing the design and implementation of hybrid optimization algorithms. Through theoretical research, it clarifies the principles of AI literacy services and hybrid optimization algorithms, identifies existing problems through current insights, and emphasizes the necessity of algorithm application. In terms of algorithm design, it completes the selection and integration of algorithms, achieving deep integration with service processes. A successful AI literacy service system based on this algorithm has been constructed, covering system architecture, key functional modules, and technology selection. The research findings are significant for enhancing the quality of AI literacy services in university libraries, and future efforts will focus on algorithm optimization and service expansion.

Keywords

Hybrid Optimization Algorithm; University Library; AI Literacy Service; System Construction

References

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