基于云优化遗传算法的自动组卷技术研究  

Automatic Generation Cloud Optimization Based on Genetic Algorithm

作　　者：邹臣嵩[1] 

机构地区：[1]广东松山职业技术学院电气工程系,韶关512126

出　　处：《计算机与数字工程》2014年第10期1842-1848,共7页Computer & Digital Engineering

基　　金：广东松山职业技术学院技术应用重点课题(编号:2012-JYKY-19)资助

摘　　要：针对传统遗传算法收敛速度慢、稳定性能差的缺陷,根据云计算思想提出一种遗传算法的考试系统组卷算法。该算法利用正态云模型的随机性和倾向性,动态调整遗传算法的个体选择适应度值和交叉概率和变异概率,以加快算法向最优解的逼近速度,可以在试题库中按照试题类型、试题数量、曝光度等约束条件进行快速搜索,系统通过选择、交叉和变异等操作,从试题库中自动地查找和组织出一些不同类型、不同难度、不同章节范围的试题来组成一套最佳的试卷,实现了快速自动组卷功能。Aiming at the defects that the traditional genetic algorithm convergence speed ,stability is poor ,based on the concept of cloud computing algorithm ,examination system for genetic algorithm is proposed .The algorithm uses the ran-domness and the tendency of the normal cloud model ,individual choice for the adjustment of genetic algorithm with dynamic fitness value and the crossover probability and mutation probability ,to speed up the algorithm convergence to the optimal so-lution ,can be in the test database according to the test question types ,quantity ,visibility constraints for rapid search ,sys-tem through selection ,crossover and mutation operation ,automatically search from the test database and organize a number of different types ,different sections ,different difficulty range the database to form a set of best papers ,to realize fast auto-matic test paper .

关 键 词：云优化 遗传算法 自动组卷 试题管理 

分 类 号：TP393.06[自动化与计算机技术—计算机应用技术]