Name
Title | ||
|---|---|---|
SCGSA: A sine chaotic gravitational search algorithm for continuous optimization problems. |
Abstract | ||
|---|---|---|
•SCGSA is inspired by SCA(sine cosine algorithm).•Sine moving pattern and k are designed to balance exploration and exploitation.•SCGSA solves the problem that CGSA is prone to suffer from local optima.•SCGSA performs well in high dimension.•The result is superior to various well-known algorithms in optimization domain. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.113118 | Expert Systems with Applications |
Keywords | Field | DocType |
Gravitational search algorithm,Chaotic maps,Sine cosine algorithm,Continuous optimization problem | Convergence (routing),Continuous optimization,Data mining,Computer science,Local optimum,Sine,Algorithm,Optimization algorithm,Chaotic,Gravitation,Gravitational search algorithm | Journal |
Volume | ISSN | Citations |
144 | 0957-4174 | 2 |
PageRank | References | Authors |
0.40 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianhua Jiang | 1 | 14 | 2.65 |
| Ran Jiang | 2 | 2 | 0.40 |
| Xianqiu Meng | 3 | 2 | 1.08 |
| Keqin Li | 4 | 2778 | 242.13 |