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