Particle swarm optimization (PSO) algorithms have low-quality initial particle swarm, which is generated by a random method when handling the problem of task scheduling in networked data centres. Such ...

However, when solving nonlinear equations, the convergence rate and solution accuracy of the existing intelligent algorithms for multilevel inverter SHEPWM will decrease with the increase of the ...

Particle swarm optimization (PSO) algorithm is an optimization technique with remarkable performance for problem solving. The convergence analysis of the method is still in research.

In this paper, based on Monte Carlo algorithm model and particle swarm optimization PSO algorithm, the optimization model of heliostatic mirror field is constructed, which is of great practical ...

Firstly, according to the distribution of the crowd, the PSO algorithm is used to cluster the target-POI of the task area, and the neural collaborative filtering algorithm is used to prioritize the ...

feature-extraction particle-swarm-optimization pso pso-algorithm lpq image-feature-extraction local-phase-quantization Updated on Feb 1, 2022 MATLAB ...

Particle Swarm Optimization (PSO) is a computational method inspired by the behavior of bird flocks or fish schools. It is used to solve optimization problems, which involve finding the best solution ...

PSO is a population-based heuristic optimization algorithm, where each “particle” in the PSO algorithm represents a potential solution, and particles move through the search space to find the optimal ...