Research on Intelligent Fixing Test Paper Algorithm Based on Cultural Algorithms and Genetic Algorithm

Author(s):  
Jiang Yong-ping ◽  
Jiang Jiao-li ◽  
Du Yu-hui ◽  
Liao Yi-ming
2014 ◽  
Vol 926-930 ◽  
pp. 3637-3640
Author(s):  
Li Feng ◽  
Qian Wu ◽  
Jing Shao Zhang

In this paper, we analyze the disadvantage of common generating test paper algorithm. An improved genetic algorithm (IGA) is proposed and used in auto-generating examination paper algorithm. We design the mathematical model of auto-generating test paper algorithm and improved the traditional GA fitness evaluation form. A computational study is carried out to verify the algorithm. Simulation results demonstrate that the performance of IGA can work efficiently than traditional ones.


2010 ◽  
Vol 37-38 ◽  
pp. 1223-1230 ◽  
Author(s):  
Zhi Feng Liu ◽  
Ji Shi ◽  
Jia Liu ◽  
Yang Li

Test paper problem is a typical multi-constrained objective optimization problem. By using genetic algorithm, this paper analyzes the initial population generation, the chromosome coding and its genetic manipulation, control parameters. Solving that by natural-coded genetic algorithm, improves test paper success rate and convergence rate. This genetic algorithm is applied successfully on NHibernate architecture, and developed "automatic test paper" Online Examination system.


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