Name
Abstract | ||
|---|---|---|
In this work a novel approach is proposed to adaptively adjust genetic operator probabilities through the adoption of a robust, real-valued optimization algorithm known as Differential Evolution (DE). We set up a series of experiments on a wide array of symbolic regression problems. The experimental results demonstrate the supremacy of our proposed method over the compared rivals both in the accuracy and reliability of the final solutions. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/SASO.2009.13 | SASO |
Keywords | Field | DocType |
wide array,novel approach,genetic operator probability,differential evolution,final solution,genetic operator,real-valued optimization algorithm,symbolic regression problem,genetic algorithms,regression analysis,mathematical model,optimization,genetics,evolutionary algorithms,evolutionary computation,evolutionary algorithm | Genetic operator,Mathematical optimization,Evolutionary algorithm,Computer science,Regression analysis,Evolutionary computation,Algorithm,Differential evolution,Self adaptation,Symbolic regression,Genetic algorithm | Conference |
ISSN | Citations | PageRank |
1949-3673 | 1 | 0.36 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatemeh Vafaee | 1 | 64 | 6.48 |
| Peter C. Nelson | 2 | 220 | 25.22 |