Statements (53)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
mathematical optimization
metaheuristic |
| gptkbp:appliesTo |
control systems
path planning robotics image processing power systems clustering feature selection data mining parameter estimation scheduling neural network training economic dispatch renewable energy optimization |
| gptkbp:category |
gptkb:evolutionary_computation
computational intelligence swarm intelligence |
| gptkbp:developedBy |
gptkb:James_Kennedy
gptkb:Russ_Eberhart |
| gptkbp:hasConcept |
position
velocity particles fitness function global best personal best |
| gptkbp:hasVariant |
gptkb:binary_particle_swarm_optimization
constriction factor PSO multi-objective PSO |
| https://www.w3.org/2000/01/rdf-schema#label |
particle swarm optimization
|
| gptkbp:inspiredBy |
social behavior of birds
social behavior of fish |
| gptkbp:introducedIn |
1995
|
| gptkbp:notablePublication |
gptkb:Kennedy,_J._and_Eberhart,_R._(1995)._Particle_Swarm_Optimization._Proceedings_of_IEEE_International_Conference_on_Neural_Networks.
|
| gptkbp:openSource |
gptkb:PSO_in_MATLAB
gptkb:PySwarms PSO in SciPy |
| gptkbp:parameter |
maximum velocity
cognitive coefficient inertia weight social coefficient swarm size |
| gptkbp:relatedTo |
differential evolution
genetic algorithm ant colony optimization |
| gptkbp:supportsAlgorithm |
stochastic
population-based |
| gptkbp:usedFor |
gptkb:machine_learning
engineering design function optimization |
| gptkbp:bfsParent |
gptkb:Fuzzy_Cognitive_Maps
gptkb:Genetic_Algorithms |
| gptkbp:bfsLayer |
6
|