摘要
提出一种改进的基因表达式编程算法,该算法具有自适应性和更好的收敛性能,并应用到函数优化中。GEP进化过程中随着进化代数的增加而自适应地增大变异率和交叉率,算法中增加适应度值反馈计算变异率和交叉率。对改进的算法进行了线性回归实验并取得很好的实验结果。实验证明该算法在函数优化中具有很好的性能。
An improved gene expression programming （GEP） algorithm is presented, the algorithm has adaptive and better astringent capability, and is applied to function optimization. In the evolution process the mutation probability and crossover probability will be increased adaptively with the increase of fitness. The feedback of fitness value to calculate the mutation probability and crossover probability, this step is added to the algorithm. Put up linear regress experiments to the improved algorithm and get a good effect. Experiments result shows that the algorithm has very good capability in function optimization.
出处
《兵工自动化》
2010年第4期90-91,94,共3页
Ordnance Industry Automation
基金
国家自然科学基金项目(60672026)资助
关键词
基因表达式编程
函数优化
变异率
交叉率
Gene expression programming
Function optimization
Mutation probability
Crossover probability
