Application research on improved particle swarm computational intelligence algorithm for multi-objective optimization in ideological and political education

Issue title: Managing Complex Computational Challenges

Guest editors: Pit Pichappan, Ezendu Ariwa and Fouzi Harrag

Article type: Research Article

Authors: Sun, Lingxiu^a | Rui, Mao^{b; *}

Affiliations: [a] Department of Economics and Management, Wuchang Institute of Technology, Wuhan, Hubei, China | [b] School of Economics and Managemen, Wuchang Institute of Technology, Wuhan, Hubei, China

Correspondence: [*] Corresponding author: Mao Rui, Department of Economics and Management, Wuchang Institute of Technology, Wuhan, Hubei, China. E-mail: armaorui@qq.com.

Abstract: In today’s world, optimization problems are becoming increasingly prominent, and the progress in optimization technologies can not only bring considerable economic benefits but also highlight their outstanding social value, making significant contributions to the sustainable development of the ecological environment. Due to their educational positioning and disciplinary development needs, local application-oriented universities overlook the optimization and development of ideological and political theory courses in their growth, leading to lagging reforms in ideological and political education and suboptimal teaching outcomes. To enhance the teaching effects of ideological and political courses in local application-oriented universities, it is essential to scientifically design class contents, actively carry out practical teaching, adapt to the needs of the times, build an “Internet + Ideological and Political Courses” online teaching platform, and continuously innovate teaching modes of ideological and political courses.

Keywords: Ideological and political education, online teaching, particle swarm computation, multi-objective optimization

DOI: 10.3233/JCM-230024

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 2061-2067, 2024