The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Facing classification problems with Particle Swarm Optimization
Applied Soft Computing
A hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
A distributed PSO-SVM hybrid system with feature selection and parameter optimization
Applied Soft Computing
Mean and variance of the sampling distribution of particle swarm optimizers during stagnation
IEEE Transactions on Evolutionary Computation
A study of particle swarm optimization particle trajectories
Information Sciences: an International Journal
Swarms in dynamic environments
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
IEEE Transactions on Evolutionary Computation
Tracking multiple targets with adaptive swarm optimization
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiple Object Tracking Via Species-Based Particle Swarm Optimization
IEEE Transactions on Circuits and Systems for Video Technology
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Locating and tracking multiple targets in the dynamic and uncertain environment is a crucial and challenging problem in many practical applications. The main task of this paper is to investigate three fundamental problems, which are composed of the identification of irregular target, locating multiple targets and tracking multiple targets. Firstly, the proposed objective function successfully gets the target's shape to discern eccentric target in the specific environment. Secondly, for the sake of locating multiple targets, the adaptive PSO algorithm divides the swarm into many subgroups, and adaptively adjusts the number of particles in each subgroup by the competition and cooperation technology. Thirdly, in order to track multiple targets in the dynamic environment, the proposed swarm optimization has the characteristic of the adaptively covered radius of the subgroup according to the minimum distance among other subgroups. To show the efficiency and high performance of the proposed algorithms, several algorithms chiefly concentrate on locating and tracking three ants in the practical systems.