In the original particle swarm optimisation (PSO) algorithm, the particles' velocities and positions are updated after the whole swarm performance is evaluated. This algorithm is also known as synchronous PSO (S-PSO). The strength of this update method is in the exploitation of the information. Asynchronous update PSO (A-PSO) has been proposed as an alternative to S-PSO. A particle in A-PSO upd...

The rest of this paper is organized as follows. Section 2 describes traditional System Identification and introduces the use of Particle Swarm Optimization (PSO) for determining the coefficients of a simple autoregressive moving average model (SwARMA). Section 3 explains Particle Swarm Optimization. Section 4 describes the results of using PSO for determining the ARMA model parameter (SwARMA) f...

Particle swarm optimization (PSO) algorithm is population-based heuristic global search algorithm inspired by social behavior patterns of organisms that live and interact within large groups. The PSO is based on researches on swarms such as fish schooling and bird flocking. Inspired by the classical PSO method and quantum mechanics theories, this work presents a quantum-inspired version of the ...

Tuning of PID controller parameters is an important problem in control field. To solve this problem we used an Advanced Particle Swarm Optimization which is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. The proposed method has fast searching speed compared to standard PSO. Furthermore this method accelerates the convergence. However...

Many engineering design problems involve a combination of both continuous and discrete variables. However, the number of studies scarcely exceeds a few on mixed-variable problems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariable nonlinear problems. PSO is an efficient method of dealing with nonlinear and non-convex optimization problems. In this pa...

Particle swarm optimization (PSO) is a well-known instance of swarm intelligence algorithms and there have been many researches on PSO. In this paper, the author proposes an extension of PSO for solving fuzzy-valued optimization problems. In the proposed extension, genotype values (i.e. values in particle position vectors) are not real numbers but fuzzy numbers. Search processes in PSO are exte...

There is a vivid trend in engineering optimization problems towards the adoption of heuristic optimization algorithms to arrive at optimal solutions. This is mainly due to the simplicity of these algorithms and the great cut down of complicated mathematical manipulations that are required in other optimization theory methods. This paper demonstrates the application of an iterative heuristic opt...

This paper presents an alternative and efficient method for solving a class of constraint parametric optimization problems using particle swarm optimization algorithm (PSO). In this paper, for the first time PSO is used for solving convex parametric programming, but PSO must be adaptive for doing it. So, for obtaining particles velocities, adaptation weight and velocity boundaries in the updati...

Particle swarm optimization (PSO) is a newer evolutionary computational method than genetic algorithm and evolutionary programming. PSO has some common properties of evolutionary computation like randomly searching, iteration time and so on. However, there are no crossover and mutation operators in the classical PSO. PSO simulates the social behavior of birds: Individual birds exchange informat...

in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...