Intelligent Generating Test Paper Based on Improved Genetic Algorithm

被引：0
|
作者：
Tang, Zhao-xia [1 ]
机构：
[1] Huaiyin Univ Technol, Dept Comp Engn, Huaan, Peoples R China
来源：
PROCEEDINGS FIRST INTERNATIONAL CONFERENCE ON ELECTRONICS INSTRUMENTATION & INFORMATION SYSTEMS (EIIS 2017) | 2017年
关键词：
genetic algorithm; cross; variation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
a new algorithm for intelligent test based on genetic algorithm is proposed in this paper. Firstly, this algorithm improves the basic genetic algorithm for two times, furthermore, the cross-probability and variation-probability of the genetic algorithm can be adjusted according to the degree of individual adaption. In this way, the individual structure of high fitness is not destroyed, and the phenomenon of slow search speed is overcome, thereby it effectively improves the speed and quality of the test paper. The experimental results show that the improved algorithm significantly improves the global optimization ability and speed, it has high robustness.
引用
收藏
页码：132 / 137
页数：6
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