|
gptkbp:instance_of
|
gptkb:Artificial_Intelligence
|
|
gptkbp:allows
|
parameter tuning
local optima
|
|
gptkbp:analyzes
|
convergence behavior
particle movement
solution space exploration
|
|
gptkbp:application
|
Optimization problems
|
|
gptkbp:developed_by
|
gptkb:James_Kennedy
Russell Eberhart
|
|
gptkbp:developer
|
gptkb:1995
|
|
gptkbp:game_components
|
gptkb:Position
velocity
particles
|
|
gptkbp:has_programs
|
metaheuristic algorithm
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Standard PSO
|
|
gptkbp:improves
|
solution quality
Adaptive PSO
Hybrid PSO
|
|
gptkbp:inspired_by
|
social behavior of birds
|
|
gptkbp:is_implemented_in
|
gptkb:MATLAB
gptkb:Java
gptkb:R
gptkb:Library
|
|
gptkbp:is_popular_in
|
gptkb:computer_science
gptkb:Research_Institute
engineering applications
|
|
gptkbp:orbital_period
|
cognitive coefficient
inertia weight
social coefficient
|
|
gptkbp:passes_through
|
gptkb:battle
|
|
gptkbp:performance
|
gptkb:military_unit
accuracy
robustness
|
|
gptkbp:propagation_method
|
gptkb:battle
|
|
gptkbp:related_to
|
gptkb:Genetic_Algorithms
Ant Colony Optimization
Differential Evolution
|
|
gptkbp:requires
|
fitness function
|
|
gptkbp:research_focus
|
algorithm efficiency
theoretical foundations
parameter optimization
application diversity
|
|
gptkbp:series
|
gptkb:battle
|
|
gptkbp:successor
|
Dynamic PSO
Multi-objective PSO
Cooperative PSO
Modified PSO
Quantum PSO
|
|
gptkbp:used_in
|
gptkb:software_framework
data mining
function optimization
neural network training
|
|
gptkbp:uses
|
swarm intelligence
|
|
gptkbp:variant
|
Swarm Intelligence
|
|
gptkbp:bfsParent
|
gptkb:Artificial_Intelligence
|
|
gptkbp:bfsLayer
|
3
|