This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is studied from the point of view of fractional calculus. In this study some initial swarm particles are randomly changed, for the system stimulation, and its response is compared with a non-perturbed reference response. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behaviour of the best particle. The dynamics is represented through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence upon the global dynamics is also analyzed. Two main issues are reported: the PSO dynamics when the system is subjected to random perturbations, a...
Abstract- This contribution deals with identification of fractional-order dynamical systems. System ...
In this paper, several feedback control methods are proposed for some real-life industrial processes...
This paper focuses on a solution technique for global optimization problems, where the objective fun...
This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is stu...
This paper studies the fractional dynamics during the evolution of a Particle Swarm Optimization (PS...
This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is stud...
The paper addresses new perspective of the PSO including a fractional block. The local gain is repl...
This work presents a new perspective of the particle swarm optimization algorithm where the integer ...
This paper proposes a novel method for controlling the convergence rate of a particle swarm optimiza...
This article reports the study of fractional dynamics during the evolution of Particle Swarm Optimiz...
The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Part...
Mathematical modeling plays an important role in biology for describing the dynamics of infectious d...
One of the most well-known bio-inspired algorithms used in optimization problems is the particle sw...
This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, s...
This article illustrates several applications of fractional calculus (FC). This paper investigates t...
Abstract- This contribution deals with identification of fractional-order dynamical systems. System ...
In this paper, several feedback control methods are proposed for some real-life industrial processes...
This paper focuses on a solution technique for global optimization problems, where the objective fun...
This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is stu...
This paper studies the fractional dynamics during the evolution of a Particle Swarm Optimization (PS...
This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is stud...
The paper addresses new perspective of the PSO including a fractional block. The local gain is repl...
This work presents a new perspective of the particle swarm optimization algorithm where the integer ...
This paper proposes a novel method for controlling the convergence rate of a particle swarm optimiza...
This article reports the study of fractional dynamics during the evolution of Particle Swarm Optimiz...
The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Part...
Mathematical modeling plays an important role in biology for describing the dynamics of infectious d...
One of the most well-known bio-inspired algorithms used in optimization problems is the particle sw...
This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, s...
This article illustrates several applications of fractional calculus (FC). This paper investigates t...
Abstract- This contribution deals with identification of fractional-order dynamical systems. System ...
In this paper, several feedback control methods are proposed for some real-life industrial processes...
This paper focuses on a solution technique for global optimization problems, where the objective fun...