基于群智能的电子学习资源过滤及收敛性分析

An analysis of E-learning resource filtering and convergence based on swarm intelligence techniques

运用基于信息素挥发因子自适应变化的蚁群算法来优化电子学习资源的组织顺序,体现群体智能在资源共享和过滤中的优势作用,并且在此基础上运用教学实例实验研究将群体智能技术应用于解决电子学习资源过滤时的收敛性问题。实验结果表明利用群体智能来组织资源可以找到和领域专家干预基本相同的解决方案,同时学生参与数不需要很多即可获得好的收敛性。

Pheromone evaluation adaptive change-based ant colony algorithm is applied to optimize the organization order of E-learning resources, which reflects the dominant role of swarm intelligence in resource sharing and filtering. On the basis of this, this paper uses teaching case experiments to study the way of solving the convergence problem in E-learning resources filtering by swarm intelligence technologies. Experimental results show that we can find out the same solution as domain experts＇ by using swarm intelligence to organ- ize resources, and get a good convergence with a small number of students＇ participation.