摘要
通用、健壮、高效的组卷算法是实现考试智能化、规范化、科学化的重要保障。本文在分析智能组卷数学模型及各种组卷算法的基础上,针对目前组卷算法存在组卷时间长、组卷效率低等缺陷,提出了一种基于模拟退火粒子群优化算法(SA-PSO)。将其应用于智能组卷实验,并与RANDOM和PSO算法作比较。实验结果表明,SA-PSO算法使得组卷效率、组卷成功率和组卷满足度等方面均有显著的提高,并且保证了组卷的质量。
The general,robust and efficient test paper generation algorithm is an important guarantee for the intelligent,standardized and scientific test. In the analysis of intelligent composing mathematical model and algorithm of generating test paper based,according to the generating set of algorithms exist long time of the test paper,test paper efficiency and low defects,puts forward a method based on simulated annealing particle swarm optimization algorithm（ SA-PSO）. Its application in intelligent test paper composition experiment,and random and PSO algorithm as the comparison experiment results show that,SA-PSO algorithm in efficiency of composing,the success rate of test and the test paper meet degree are increased significantly,and to ensure the quality of the test paper.
出处
《长春师范大学学报》
2016年第10期42-46,共5页
Journal of Changchun Normal University
基金
2015年安徽省高等学校省级自然科学研究重点基金项目"物联网技术在中药材种植环境信息采集中的研究与应用"(KJ2015A417)
2015年安徽省高校振兴计划优秀青年人才支持计划(gxyq ZD2016529)
2015年安徽省科技攻关计划项目"基于OTO模式的中药材诚信平台研究"(1501zc03031)
关键词
模拟退火法
粒子群
智能组卷
simulated annealing
particle swarm
intelligent test paper
