At low bitrate and with acceptable quality in Fractal Image Compression (FIC) of the coded image, the encoding time is very large for most existing algorithms. In this paper, a fast fractal encoding system is proposed using particle swarm optimization (PSO) to reduce the encoding time. Here, an optimization technique is used for the MSE based on the stopping criterion between range block and do...

This paper presents an application of particle swarm optimization (PSO) to the grounding grid planning which compares to the application of genetic algorithm (GA). Firstly, based on IEEE Std.80, the cost function of the grounding grid and the constraints of ground potential rise, step voltage and touch voltage are constructed for formulating the optimization problem of grounding grid planning. ...

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the...

The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overc...

estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

This paper presents a Hybrid Particle Swarm Optimization (HPSO) method for solving the Task Assignment Problem (TAP) which is an np-hard problem. Particle Swarm Optimization (PSO) is a recently developed population based heuristic optimization technique. The algorithm has been developed to dynamically schedule heterogeneous tasks on to heterogeneous processors in a distributed setup. Load balan...

The optimal design of planar multilayered electromagnetic wave absorbers is presented. The optimization process is based on an improved particle swarm optimization (PSO). Assumed that the number of layers is given, in order to obtain an ideal absorber which is thin and has a low reflection coefficient within a wide band of frequencies, the thickness of each layer needs to be optimized as well t...

This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...

In order to improve the convergence speed and the drawback of easily converging to the local optimum of the standard particle swarm optimization (PSO), two improved PSO algorithms are presented based on the simple particle swarm optimization algorithm without speed attribute. One is introducing differential mutation technology of differential evolution algorithm into the simple PSO algorithm fo...

Particle Swarm Optimization (PSO) is an innovative and competitive optimization technique for numerical optimization with real-parameter representation. This paper examines the working mechanism of PSO in a principled manner with forma analysis and investigates the applicability of PSO on the Quadratic Assignment Problem (QAP). Particularly, the derived PSO operator for QAP is empirically studi...