Particle swarm optimization algorithm: an overview
D Wang, D Tan, L Liu - Soft computing, 2018 - Springer
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm
motivated by intelligent collective behavior of some animals such as flocks of birds or …
motivated by intelligent collective behavior of some animals such as flocks of birds or …
Quantum-behaved particle swarm optimization: analysis of individual particle behavior and parameter selection
Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from
quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization …
quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization …
Stability analysis of the particle dynamics in particle swarm optimizer
V Kadirkamanathan, K Selvarajah… - IEEE Transactions on …, 2006 - ieeexplore.ieee.org
Previous stability analysis of the particle swarm optimizer was restricted to the assumption
that all parameters are nonrandom, in effect a deterministic particle swarm optimizer. We …
that all parameters are nonrandom, in effect a deterministic particle swarm optimizer. We …
Convergence analysis and improvements of quantum-behaved particle swarm optimization
Motivated by concepts in quantum mechanics and particle swarm optimization (PSO),
quantum-behaved particle swarm optimization (QPSO) was proposed as a variant of PSO …
quantum-behaved particle swarm optimization (QPSO) was proposed as a variant of PSO …
[图书][B] Particle swarm optimisation: classical and quantum perspectives
Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters
and is computationally simple and easy to implement, it is not a globally convergent …
and is computationally simple and easy to implement, it is not a globally convergent …
Modified central force optimization (MCFO) algorithm for 3D UAV path planning
Y Chen, J Yu, Y Mei, Y Wang, X Su - Neurocomputing, 2016 - Elsevier
Path planning for the three-dimensional (3D) unmanned aerial vehicles (UAV) is a very
important element of the whole UAV autonomous control system. In this paper, a modified …
important element of the whole UAV autonomous control system. In this paper, a modified …
From particle swarm optimization to consensus based optimization: stochastic modeling and mean-field limit
S Grassi, L Pareschi - Mathematical Models and Methods in Applied …, 2021 - World Scientific
In this paper, we consider a continuous description based on stochastic differential
equations of the popular particle swarm optimization (PSO) process for solving global …
equations of the popular particle swarm optimization (PSO) process for solving global …
Particle swarm optimization for feature selection: A review of filter-based classification to identify challenges and opportunities
M Cherrington, D Airehrour, J Lu… - 2019 IEEE 10th …, 2019 - ieeexplore.ieee.org
Feature selection (FS) is a fundamental big data task, improving classification performance
by selecting a relevant feature subset to mitigate thecurse of dimensionality'. As the number …
by selecting a relevant feature subset to mitigate thecurse of dimensionality'. As the number …
A modified PSO structure resulting in high exploration ability with convergence guaranteed
Particle swarm optimization (PSO) is a population-based stochastic recursion procedure,
which simulates the social behavior of a swarm of ants or a school of fish. Based upon the …
which simulates the social behavior of a swarm of ants or a school of fish. Based upon the …
Random drift particle swarm optimization algorithm: convergence analysis and parameter selection
The random drift particle swarm optimization (RDPSO) algorithm is a PSO variant inspired
by the free electron model in metal conductors placed in an external electric field. Based on …
by the free electron model in metal conductors placed in an external electric field. Based on …