摘要
因为传统组卷方法的时间和空间开销大、成功率较低,简单遗传算法的收敛速度慢、稳定性差,所以提出了基于改进遗传算法的智能组卷方法,通过根据个体适应度值自适应地选择个体,调整交叉概率和变异概率等措施,加快了算法向最优解的逼近速度,提高了组卷的效率和成功率。论文介绍了该组卷方法的组卷策略,数学模型,各模块的详细设计。
The traditional Generating Examination Paper method has disadvantages of large time and space consumption,and low success rate.The simple generic algorithm has disadvantages of slow convergence speed and poor stability.So an intelligent test construction method based on improved generic algorithm is proposed.The intelligent method adaptively selects individuals and adjusts the crossover and mutation probabilities based on individual fitness,which accelerates approximation speed to the optimal solution and improves the efficiency and success rate.This paper will introduce the test construction strategies,mathematical model,and the detailed design of each module.
出处
《计算机与数字工程》
2013年第2期176-178,207,共4页
Computer & Digital Engineering
关键词
改进遗传算法
智能组卷
自适应
improved genetic algorithm
intelligent generating examination paper
adaptive
