[1]楼玉萍 金炳尧 骆红波.PBIL进化算法在自动组卷系统中的应用[J].计算机技术与发展,2006,(06):80-82.
 LOU Yu-ping,JIN Bing-yao,LUO Hong-bo.Application of PBIL Algorithm in Automatic Test Paper Construction[J].,2006,(06):80-82.
点击复制

PBIL进化算法在自动组卷系统中的应用()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2006年06期
页码:
80-82
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Application of PBIL Algorithm in Automatic Test Paper Construction
文章编号:
1673-629X(2006)06-0080-03
作者:
楼玉萍12 金炳尧1 骆红波1
[1]浙江师范大学信息学院[2]国防科技大学计算机学院
Author(s):
LOU Yu-pingJIN Bing-yao LUO Hong-bo
[1]College of Information Science and Engineering, Zhejiang Normal University[2]College of Computer, National University of Defense Technology
关键词:
进化计算PBIL算法组卷问题
Keywords:
evolutionary computationPBIL algorithm test paper construction problem
分类号:
TP301.6
文献标志码:
A
摘要:
进化计算是一种搜索方法,广泛用于求解各类优化问题。PBIL算法将进化获得的知识——学习概率用以指导后代的产生,使搜索更具方向性,因而往往能取得更好的效果。自动组卷问题是一个典型的组合优化问题。文中针对PBIL算法的特点,设计了一个自动组卷求解方案,并用实验数据进行计算。结果表明;该算法计算速度快、稳定性好,尤其是在约束条件比较多的情况下,显示出算法的高适应性,是解决组卷问题较为理想的算法
Abstract:
Evolutionary computation is a search method,which has been applied in solving optimization problems. PBIL algorithm instructs the generation of offspring through knowledge acquired from evolutionary, namely, learning probability, and makes the searching in the right direction. So can get the better result. Automatic test paper construction is a typical optimization problem. The paper brings forward an automatic test paper construetion solution through PBIL algorlthm, and evolutionary computation is realized by experiment data. The result shows that the algorithm has high - speed and good- stability. Especially under the condition with many limits, the algorithm shows that it is more adaptive and it is an ideal algorithm for solving the problem of paper organization

相似文献/References:

[1]柳秋云 王翰虎.基于基因表达式编程的核k近邻分类算法[J].计算机技术与发展,2009,(08):19.
 LIU Qiu-yun,WANG Han-hu.A Kernel KNN Classifier Based on Gene Expression Programming[J].,2009,(06):19.
[2]齐仲纪 刘漫丹.文化算法研究[J].计算机技术与发展,2008,(05):126.
 QI Zhong-ji,LIU Man-dan.Study on Cultural Algorithms[J].,2008,(06):126.
[3]陆克中 张秋华 孙兰娟.一种改进的粒子群优化算法及其仿真[J].计算机技术与发展,2007,(11):88.
 LU Ke-zhong,ZHANG Qiu-hua,SUN Lan-juan.An Improved Particle Swarm Optimization and Simulation[J].,2007,(06):88.
[4]张庆红 程国建.基于遗传算法的神经网络性能优化[J].计算机技术与发展,2007,(12):125.
 ZHANG Qing-hong,CHENG Guo-jian.Neural Network Optimization Based on Genetic Algorithms[J].,2007,(06):125.

备注/Memo

备注/Memo:
楼玉萍(1963-),女,浙江东阳人,讲师,硕士,研究方向为软件工程理论和信息教育技术
更新日期/Last Update: 1900-01-01