Abstract

Abstract The emergence of a new industrial form, online education, has opened up an efficient and convenient learning channel for people. In this paper, the basic process and algorithmic ideas of the migratory bird algorithm are investigated, and the optimization is carried out by using a simulated annealing method for its problem of finding the optimal global solution too slowly, adding the inner loop of SA at each generation of particle swarm update, and improving the fitness value function and update criterion of each particle in the particle swarm based on the outer loop. Then, the online education model of this paper is designed based on the SA-PSO algorithm. For the evaluation of interaction quality, this model obtains a comprehensive evaluation index of 0.856, which is 10.24% higher than New Oriental and 18.65% higher than NetEase Cloud Classroom. In terms of service quality, the overall evaluation index of this model is 8.73% higher than that of New Oriental and 20.35% higher than NetEase Cloud Classrooms. In terms of system quality, the overall evaluation index of this model is 4.31% higher than that of New Oriental and 18.69% higher than NetEase Cloud Classrooms. This study proposes rationalized improvement strategies for the limitations of the existing online education model, and the model based on the SA-PSO algorithm helps to promote the quality of online education.

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