节点文献
Grid-Based Pseudo-Parallel Genetic Algorithm and Its Application
【Abstract】 Aimed at the problems of premature and lower convergence of simple genetic algorithms (SGA), three ideas——partition the whole search uniformly, multi-genetic operators and multi-populations evolving independently are introduced, and a grid-based pseudo-parallel genetic algorithms (GPPGA) is put forward. Thereafter, the analysis of premature and convergence of GPPGA is made. In the end, GPPGA is tested by both six-peak camel back function, Rosenbrock function and BP network. The result shows the feasibility and effectiveness of GPPGA in overcoming premature and improving convergence speed and accuracy.
【关键词】 genetic algorithms;
parallel;
grid;
neural network;
weights optimizing;
【Key words】 genetic algorithms; parallel; grid; neural network; weights optimizing;
【Key words】 genetic algorithms; parallel; grid; neural network; weights optimizing;
【基金】 theNationalNaturalScienceFundationofChina(60171018)
- 【文献出处】 Journal of Beijing Institute of Technology(English Edition) ,北京理工大学学报(英文版) , 编辑部邮箱 ,2006年01期
- 【分类号】TP18
- 【被引频次】2
- 【下载频次】19