Title :
Research on test paper auto-generating based on immune genetic algorithm
Author :
Yan-cong, Zhou ; Jun-hua, Gu ; Xiao-chen, Sun ; Yong-feng, Dong ; Ming, Fan
Author_Institution :
Tianjin Univ. of Commerce, Hebei Univ. of Technol., Tianjin, China
Abstract :
In order to improve the auto-generating test paper´s quality at the cost of low time, an intelligent algorithm based on immune genetic algorithm was proposed. In the algorithm immune process was added into the basic framework of genetic algorithm, and the algorithm based on vaccination was put forward and used for test paper auto-generating. The problem that genetic algorithm is precocity and easy to fall into a local optimization was resolved by this algorithm. The feasibility and validity of the algorithm was proved by test data compared with other algorithms. At last the validating system enhances the users´ condition constraints for test paper through manual inching, thus the system is more simple and practical.
Keywords :
educational administrative data processing; genetic algorithms; auto-generating test paper quality; immune genetic algorithm; intelligent algorithm; manual inching; Computers; Convergence; Databases; Genetic algorithms; Optimization; Testing; Vaccines; Genetic algorithm; Immune algorithm; Local convergence; Test paper auto-generating; Vaccination;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968629