In order to improve performance of particle swarm optimization algorithm (PSO) in global optimization, the reason of premature convergence of the PSO is analyzed, and a new particle swarm optimization based on two subswarms (TSS-PSO) is proposed in this paper. The particle swarm is divided into two identical sub-swarms, that is, the first sub-swarm adopts basic PSO model to evolve, whereas the ...

In this paper a mesh-free model of the functionally graded material (FGM) plate is presented.  The piezoelectric material as a sensor and actuator has been distributed on the top and bottom of the plate, respectively. The formulation of the problem is based on the classical laminated plate theory (CLPT) and the principle of virtual displacements. Moreover, the Particle Swarm optimization (PSO) ...

A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO) algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for m...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

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...

-Particle Swarm Optimization (PSO) has received increased attention in the evolutionary computation fields recently. In the paper, we proposed Adaptive constriction factor for Location-related Particle Swarm (ALPS) that is shown to be superior when compared with the existing PSO algorithm. We adapt a technique of overcoming complex problems with PSO. This is accomplished by using the ratio of t...

Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of...

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

Particle Swarm Optimization (PSO) is proposed in our research to generate Fuzzy Controller, a fuzzy logic control (FLC) is proposed to control manufacturing system presented by mmachine line as an m-order state-space. As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic contro...

We propose a novel generalized algorithmic framework to utilize particle filter for optimization incorporated with the swarm move method in particle swarm optimization (PSO). In this way, the PSO update equation is treated as the system dynamic in the state space model, while the objective function in optimization problem is designed as the observation/measurement in the state space model. Part...