Name
Abstract | ||
|---|---|---|
Nature inspired algorithms implement successful optimization and adaptation strategies observed in the nature. Various bio-inspired algorithms mimic the behavioural patterns of plants, animals, their communities and their evolution. Surprisingly, the behavioural patterns and survival strategies of protozoa, one of the most prevalent and successful species on Earth, did not receive significant attention from the bio-inspired computing community until present time. This study proposes a new variant of Particle Swarm Optimization incorporating behaviour inspired by protozoa and evaluates the performance of such an algorithm on a set of well known test functions. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.347 | SMC |
Keywords | Field | DocType |
significant attention,particle swarm optimization,behavioural pattern,new variant,successful species,bio-inspired computing community,protozoic behaviour,various bio-inspired algorithm,successful optimization,present time,adaptation strategy | Particle swarm optimization,Computer science,Multi-swarm optimization,Artificial intelligence,Machine learning,Metaheuristic,Swarm robotics | Conference |
ISSN | Citations | PageRank |
1062-922X | 1 | 0.37 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Václav Snáel | 1 | 37 | 10.63 |
| Krömer Pavel | 2 | 330 | 59.99 |
| Ajith Abraham | 3 | 8954 | 729.23 |