Application of Swarm Intelligence Algorithms in Higher Vocational Teaching

College Chinese," as a core course in literary majors, faces challenges in achieving its intended goals due to the limitations of traditional teacher-centred teaching methods and students' lack of enthusiasm.This study adopts genetic algorithms, particle swarm algorithms, hybrid frog-leaping methods, and swarm intelligence optimization algorithms to improve this situation.Through practical application, it is found that these methods outperform traditional manual and composite methods.However, in-depth research reveals that swarm intelligence algorithms have lower solving efficiency.To better meet practical application needs, a series of convergence and precision adjustments are applied to the results obtained by the swarm intelligence algorithms.Furthermore, improvements are made to the hybrid frog-leaping algorithm to cater to various engineering improvement requirements.Using artificial intelligence algorithms to guide classroom activities expands students' thinking and inspires their minds to better cope with multiple complex engineering challenges.