DocumentCode :
2862375
Title :
Research on Intelligent Auto-Generating Test Paper Based on Improved Genetic Algorithms
Author :
Wu Xiaoqin ; Song Yin
Author_Institution :
Key Lab. of Network & Intell. Inf. Process., Hefei Univ., Hefei, China
fYear :
2009
fDate :
11-13 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
The constraint conditions of the auto-generating test paper are analyzed. The mathematical model of intelligence test paper generation system is set up and a new method of composing test paper based on the improved genetic algorithm is given. The result of the experiments shows that the new method is more efficient and easier to deal with the problem of autogenerating test paper than the traditional algorithms. Autogenerating test paper has the advantages of high success rate and fast speed, and better performance and practicability.
Keywords :
educational administrative data processing; genetic algorithms; auto generating test paper constraint condition; improved genetic algorithm; intelligent auto generating test paper; Algorithm design and analysis; Convergence; Genetic algorithms; Information analysis; Information processing; Intelligent networks; Laboratories; Mathematical model; Microelectronics; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
Type :
conf
DOI :
10.1109/CISE.2009.5366125
Filename :
5366125
Link To Document :
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