In this paper an extensive theoretical and empirical analysis of recently introduced Particle Swarm Optimization algorithm with Convergence Related parameters (CR-PSO) is presented. The convergence of the classical PSO algorithm is addressed in detail. The conditions that should be imposed on parameters of the algorithm in order for it to converge in mean-square have been derived. The practical...

In this paper, parameter extraction for PSP MOSFET model is demonstrated using Particle Swarm Optimization (PSO) algorithm. I-V measurements are taken on 65 nm technology NMOS devices. For the purpose of comparison, parameter extraction is also carried out using Genetic Algorithm (GA). It is shown that PSO algorithm gives better agreement between measurements and model in comparison to GA and w...

In the paper a modified particle swarm optimization (MPSO) is proposed where concepts from firefly algorithm (FA) are borrowed to enhance the performance of particle swarm optimization (PSO). The modifications focus on the velocity vectors of the PSO, which fully use beneficial information of the position of particles and increase randomization item in the PSO. Finally, the performance of the p...

A new filtering algorithm — PSO-UPF was proposed for nonlinear dynamic systems. Basing on the concept of re-sampling, particles with bigger weights should be re-sampled more time, and in the PSO-UPF, after calculating the weight of particles, some particles will join in the refining process, which means that these particles will move to the region with higher weights. This process can be regard...

this study on the design of pid controllers for flexible single-arm robot system optimizationpso method is focused so that the coefficients of the pid controller are reduced. in this study,pid controller and pso algorithm have been described and then by using matlab, pidcontrol was simulated. then by pso algorithm, attempts to reduce the pid coefficients are givenby simulation. finally pid coef...

In this paper, an artificial neural network (ANN) based on hybrid algorithm combining particle swarm optimization (PSO) with back-propagation (BP) is proposed to forecast the daily streamflows in a catchment located in a semi-arid region in Morocco. The PSO algorithm has a rapid convergence during the initial stages of a global search, while the BP algorithm can achieve faster convergent speed ...

The paper presents a novel particle swarm optimizer (PSO), called gender-hierarchy particle swarm optimizer based on punishment (GH-PSO). In the proposed algorithm, the social part and recognition part of PSO both are modified in order to accelerate the convergence and improve the accuracy of the optimal solution. Especially, a novel recognition approach, called general recognition, is presente...

PSO algorithm is an intelligent optimization algorithm based on swarm intelligence. Particle swarm optimization algorithm is simple, easy to implement, and it has a wide application prospect in scientific research and engineering applications. In real life, most of the optimization problem is the optimization problem of some nonlinear discrete with the existence of local. PSO algorithm also has...

This paper proposes a hybrid Particle Swarm Optimization (PSO) method, which is based on the fusion of the PSO, Clonal Selection Algorithm (CSA), and Mind Evolutionary Computation (MEC). The clone function borrowed from the CSA and MEC-characterized similartaxis and dissimilation operations are embedded in the original PSO algorithm. Simulations of nonlinear function optimization are made to co...