一种智能选课算法的研究与实现

Research and Implementation of Intelligent Choosing Courses Algorithm

现有的选课系统更多的关心负载及公平,忽视合理及效率。基于BP神经网络,建立了一种新的智能选课模型,提出了分类因子,参照因子,侧重比等定义。通过对所有课程进行分类,比较同一类别中各课程的权值差和权值方差,求解出具有最大相似度的解,即最能满足学生需要的课程,从而调动学生学习积极性,合理安排选课。算法的可行性,有效性在某大学选课系统中得到了验证。

The current choosing courses system is more concerned about load and fairness than rationality and efficiency. This paper proposed a novel intelligent choosing courses model based on BP neural network. And a lot of definitions such as classification coefficient, proportion value and emphasize value are proposed. First classify all courses, compare the weight subtraction and variation subtraction in a same type, then compute the max-similarity value, which student needs most. So the study enthusiasm can be consequently improved and lessons can be arranged suitably. This algorithm is proved effective and feasible in some choosing courses system.