Research and Analysis on the Evaluation of University Fusion System Based on Dynamic Group Strategy Teaching Optimization Algorithm

Shang Xiaomei, Zeng Hui, Otilia Manta
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Abstract

Dynamic group strategy teaching optimization algorithm can simulate the natural evolution process to find the optimal teaching mix. This study uses the algorithm to constantly iterate the process characteristics to generate a new teaching strategy mix, and carries out an application analysis on the teaching mix. 662 students from 5 universities are tested by scale s. The process of S PPS is used to analyze and evaluate the recovered data. The results show that the algorithm can effectively improve the overall quality of talent training, and provide a reference direction for constructing a multi-dimensional integrated education model and exploring a new path for students' all-round development.
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基于动态群体策略教学优化算法的高校融合系统评价研究与分析
动态群体策略教学优化算法可以模拟自然进化过程,找到最优的教学组合。本研究利用该算法不断迭代过程特征生成新的教学策略组合,并对该教学策略组合进行应用分析。采用s量表对5所高校的662名学生进行测试,采用s PPS过程对恢复的数据进行分析和评价。结果表明,该算法能够有效提高人才培养的整体质量,为构建多维度的一体化教育模式,探索学生全面发展的新路径提供参考方向。
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