Name
Abstract | ||
|---|---|---|
•A novel feature selection approach based on binary Salp Swarm Algorithm (SSA) is proposed.•Asynchronous updating rules and leadership structure were used to adapt the salps’ positions.•The number of leaders in the social organization of the artificial salp chain is well studied.•The salp chain is divided into several sub-chains.•The salps in each sub-chain can follow a different strategy to adaptively update their locations. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.asoc.2018.07.040 | Applied Soft Computing |
Keywords | Field | DocType |
Swarm Intelligence,Salp Swarm Algorithm,SSA,Wrapper feature selection,Optimization,Machine learning,Classification | Information system,Asynchronous communication,Feature selection,Swarm intelligence,Preprocessor,Artificial intelligence,Salp,Machine learning,Salp swarm algorithm,Mathematics,Binary number | Journal |
Volume | ISSN | Citations |
71 | 1568-4946 | 27 |
PageRank | References | Authors |
0.58 | 38 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibrahim Aljarah | 1 | 703 | 33.62 |
| Majdi Mafarja | 2 | 574 | 20.00 |
| Ali Asghar Heidari | 3 | 379 | 23.01 |
| Hossam Faris | 4 | 761 | 38.48 |
| Yong Zhang | 5 | 438 | 103.95 |
| Seyedali Mirjalili | 6 | 3949 | 140.80 |