DocumentCode
3733810
Title
Research on Test Paper Auto-generating Based on Improved Particle Swarm Optimization
Author
Chong Zhang;Jing Zhang
Author_Institution
Tianjin Polytech. Univ., Tianjin, China
fYear
2015
Firstpage
92
Lastpage
96
Abstract
The existing algorithm of generating test paper has the problem of low efficiency and slow convergence rate, etc. Improved particle swarm algorithm for test paper auto-generating is proposed on the basic of the particle swarm optimization algorithm and improved genetic algorithm. The algorithm uses greedy algorithm to optimize the initial population. The crossover and mutation operator of genetic algorithm are used to avoid the local convergence of population during the process of iteration. Experimental results show that the improved particle swarm optimization algorithm can applied to auto-generating test paper, which has faster speed and higher success rate.
Keywords
"Parallel architectures","Programming"
Publisher
ieee
Conference_Titel
Parallel Architectures, Algorithms and Programming (PAAP), 2015 Seventh International Symposium on
ISSN
2168-3042
Type
conf
DOI
10.1109/PAAP.2015.27
Filename
7387307
Link To Document