基于改进遗传算法的解剖类课程组卷研究

Research on Anatomy Course Paper Formation Based on Improved Genetic Algorithm

在系统解剖和局部解剖课程教学过程中,应用信息化技术提高课程教学效果已经成为医学院采用的重要手段。文章以系统解剖和局部解剖课程题库为例,对系统组卷算法效率进行了研究。首先根据题库模型和文献分析,选取遗传算法对题库模型生成试卷,通过现有遗传算法进行测试验证,获取变异概率基准值;其次,为了使试卷个体快速达到适应度和相关参数要求,基于变异概率的基准值,提出了特定区间内动态调整变异概率的方法;最后,在解剖类课程题库的基础上进行测试,相比于其他改进的遗传算法。测试结果表明生成试卷的速度和质量都得到了提升。

In the course of systematic anatomy and partial anatomy teaching,the application of information technology to improve the teaching effect has become an important means adopted by medical colleges.In this paper,we study the efficiency of system test paper formation algorithm by taking the question bank of system anatomy and local anatomy as examples.Firstly,according to the question bank model and literature analysis,genetic algorithm is selected to generate the question bank model,and the existing genetic algorithm is tested and verified to obtain the reference value of mutation probability.Secondly,in order to make the test paper quickly meet the requirements of fitness and related parameters,based on the reference value of mutation probability,the method of dynamic adjustment of mutation probability in a specific interval is proposed.Finally,the paper is tested on the basis of anatomy course question bank.Compared with other improved genetic algorithms,the speed and quality of test paper generation are improved,and the effectiveness of the improved algorithm is verified.