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计算机工程 ›› 2011, Vol. 37 ›› Issue (14): 161-163. doi: 10.3969/j.issn.1000-3428.2011.14.053

• 人工智能及识别技术 • 上一篇    下一篇

自适应遗传算法在智能组卷中的应用

黄宝玲   

  1. (柳州职业技术学院信息工程系,广西 柳州 545006)
  • 收稿日期:2011-01-12 出版日期:2011-07-20 发布日期:2011-07-20
  • 作者简介:黄宝玲(1976-),女,讲师、硕士,主研方向:智能化信息管理
  • 基金资助:
    教育部高职高专计算机类专业立项课题基金资助项目(jzw59010826)

Application of Adaptive Genetic Algorithm in Intelligent Test Paper Composition

HUANG Bao-ling   

  1. (Department of Information Engineering, Liuzhou Vocational & Technological College, Liuzhou 545006, China)
  • Received:2011-01-12 Online:2011-07-20 Published:2011-07-20

摘要: 传统遗传算法在组卷过程中存在收敛速度慢、迭代次数多,以及采用固定遗传概率在遗传操作中极易破坏高适应性个体等问题。为此,提出一种用于提高组卷效率的自适应遗传算法。根据组卷参数的不同,采用有侧重的不完全随机搜索策略,针对低适应性个体借助交叉、变异算子进行快速淘汰,同时在迭代过程中增加最优个体保存机制,以较小的运算代价获得较高的组卷效率。实验结果表明,该算法在迭代次数、运行时间和组卷准确性方面均优于传统算法。

关键词: 自适应, 遗传算法, 智能组卷, 遗传操作, 试卷定制

Abstract: In order to overcome the slow convergence rate, too much number of iterations and the fixed heredity probability is extremely easy in the heredity operation to destroy questions and so on high compatible individual. According to the differences of the parameters of the generating papers, this paper uses incomplete random searching strategy. For the low adaptability of individual, it uses crossover, mutation operators for rapid elimination. As the meanwhile, it uses an iterative process to increase the best individual saving mechanisms and to decrease the cost of the high computing efficiency of the generating paper. Experimental result indicates that compared with traditional algorithm, the adaptive genetic algorithm has the characteristics such as fast convergence rate, high speed of running times and more accuracy of generating papers.

Key words: adaptive, Genetic Algorithm(GA), intelligent test paper composition, genetic manipulation, test paper customization

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