基于遗传算法的组卷技术研究与改进
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摘要
优化了自动组卷的约束条件,并针对知识点的考核层次问题进行了算法改进。在初始化种群时使用知识点权重分级表,按知识点权重顺序来选取试题生成初始种群中的染色体,使种群从最初时起就满足对知识点的考核层次要求,并在遗传算子的设计中保持了种群知识点的稳定性。结果表明,改进算法在保证知识点覆盖率的同时,能提高重要知识点的覆盖率。
The constraints of automatic test paper are optimized,and the algorithm is improved according to the examination hierarchy of knowledge points.The knowledge points weight grading table is used when initializing the population,and the chromosomes in the initial population are selected according to the knowledge weight order so that the population can meet the requirement of the assessment level of the knowledge points from the initial time.In the design of the genetic operators maintains the stability of the population of knowledge point.The results show that the improved algorithm can improve the coverage rate of important knowledge points while guaranteeing the coverage of knowledge points.
The constraints of automatic test paper are optimized,and the algorithm is improved according to the examination hierarchy of knowledge points.The knowledge points weight grading table is used when initializing the population,and the chromosomes in the initial population are selected according to the knowledge weight order so that the population can meet the requirement of the assessment level of the knowledge points from the initial time.In the design of the genetic operators maintains the stability of the population of knowledge point.The results show that the improved algorithm can improve the coverage rate of important knowledge points while guaranteeing the coverage of knowledge points.
引文
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[2]Chen L H,Mei Y D,Dong Y J,et al.Improved genetic algorithmand its application in optimal dispatch of eas-cade reservoirs[J].Journal of Hydraulic Engineering,2008,38(5):550-556.
[3]黄宝玲.自适应遗传算法在智能组卷中的应用[J].计算机工程,2011,37(14):161-163.
[4]梁亚澜,聂长海.覆盖表生成的遗传算法配置参数优化[J].计算机学报,2012,35(7):1522-1538.
[5]朱婧,戴青云,王美林,等.自适应遗传算法在工程训练在线考试中的应用[J].计算机工程与应用,2013,49(14):227-230.
[6]Wang L,Tang D.An improved adaptive genetic algorithm based on hormone modulation mechanism for job-shop scheduling problem[J].Expert Systems with Applications,2011,38(6):7243-7250.
[7]陈国彬,张广泉.基于改进遗传算法的快速自动组卷算法研究[J].计算机应用研究,2015,32(10):2996-2998.
[8]张琨,杨会菊,宋继红,等.基于遗传算法的自动组卷系统的设计与实现[J].计算机工程与科学,2012,34(5):178-183.
[9]鲁萍,王玉英.多约束分级寻优结合预测计算的智能组卷策略[J].计算机应用,2013,33(2):342-345.
[10]贺荣,陈爽.在线组卷策略的研究与设计[J].计算机工程与设计,2011,32(6):2183-2186.
[11]任剑,卞灿,全惠云.基于层次分析方法与人工鱼群算法的智能组卷[J].计算机应用研究,2010,27(4):1293-1296.
[12]鲁萍,何宏璧,王玉英.智能组卷中分级带权重知识点选取策略[J].计算机应用与软件,2014,31(3):67-69.