Since chaos systems generally have the intrinsic properties of sensitivity to initial conditions, topological mixing and density of periodic orbits, they may tactfully use the chaotic ergodic orbits to achieve the global optimum or their better approximation to given cost functions with high probability. During the past decade, they have increasingly received much attention from academic commun...

In this paper a novel invisible robust watermarking scheme for embedding and extracting a digital watermark in an image is presented. The novelty lies in determining perceptually important coefficients of transform in the host image using simple Haar Wavelet Transform (HWT) and Genetic Algorithm(GA)-Particle Swarm Optimization(PSO) based hybrid optimization. Invisible watermark is embedded such...

Introduction Studies document rod fracture in pedicle subtraction osteotomy (PSO) settings where disk spaces were preserved above or adjacent to the PSO. This study compares the multidirectional bending rigidity and fatigue life of PSO segments with or without interbody support. Methods Twelve specimens received bilateral T12-S1 posterior fixation and L3 PSO. Six received extreme lateral interb...

Adaptive Particle Swarm Optimization (PSO) variants have become popular in recent years. The main idea of these adaptive PSO variants is that they adaptively change their search behavior during the optimization process based on information gathered during the run. Adaptive PSO variants have shown to be able to solve a wide range of difficult optimization problems efficiently and effectively. In...

Psoriasis (Pso) is a common chronic cutaneous inflammatory disease involving the skin that is associated with serious comorbidities. Comorbidities in Pso include psoriatic arthritis (PsA), reduced quality of life, malignancy, depression, but also a constellation of associated conditions that enhance the cardiovascular (CV) risk. Indeed, obesity is common in patients with Pso or PsA and is consi...

Particle Swarm Optimization (PSO) has been extensively used in recent years for the optimization of nonlinear optimization problems. Two of the most popular variants of PSO are PSO-W (PSO with inertia weight) and PSO-C (PSO with constriction factor). Typically particles in swarm use information from global best performing particle, gbest and their own personal best, pbest. Recently, studies hav...

In simulation-based design optimization, one of the greatest challenges is the intensive computing burden. In order to reduce the computational time, a parallel implementation of the particle swarm optimization (PSO) algorithm on graphic processing unit (GPU) is presented in this paper. Instead of executed on the central processing unit (CPU) in a serial manner, the PSO algorithm is executed in...

In this paper a new method for dynamic parameter adaptation in particle swarm optimization (PSO) is proposed. PSO is a metaheuristic inspired in social behaviors, which is very useful in optimization problems. In this paper we propose an improvement to the convergence and diversity of the swarm in PSO using fuzzy logic. Simulation results show that the proposed approach improves the performance...

We investigate the runtime of the Binary Particle Swarm Optimization (PSO) algorithm introduced by Kennedy and Eberhart (1997). The Binary PSO maintains a global best solution and a swarm of particles. Each particle consists of a current position, an own best position and a velocity vector used in a probabilistic process to update the particle’s position. We present lower bounds for a broad cla...