In this study, an improved method based on evolutionary algorithms for denoising of satellite images is proposed. In this approach, the stochastic global optimisation techniques such as Cuckoo Search (CS) algorithm, artificial bee colony (ABC), and particle swarm optimisation (PSO) technique and their different variants are exploited for learning the parameters of adaptive thresholding function...

This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and ro...

Traditional mean-shift tracking algorithm use pre-defined tracking feature. Its trends to lead tracking failure in the complex background scenes and fast-changing background scenes. In this paper, an improved mean-shift tracking algorithm using Particle swarm optimization (PSO) based adaptive feature selection is presented to improve the tracking performance. We assume that the features with be...

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and...

The image de-noising is one in all the foremost studied areas within the field of image processing. There are many ways (like communication channel, imperfect sensors, interference etc.) by which the noise may affect the image. Depending upon the nature of noise and the image many techniques has been already proposed. However for any technique it is difficult to operate on different level of no...

To provide cost-effective communication systems for separate a signal into different frequency region and eliminate adverse signals and harmonics, Fuzzy Adaptive Modified particle swarm optimization (FAMPSO) method was used to have an optimized gain ripple of 6 order elliptic low pass filter with 300 MHz cut-off frequency. The feasibility and effectiveness of the FAMPSO algorithm is demonstrate...

Abstract— The aim of this paper is to study the tuning of a PID controller using swarm optimization techniques. In this paper, comparative performance of PSO and BF-PSO based PID controller is analyzed. PSO algorithm converges rapidly during the initial stages of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance t...

A new model for evolving the structure of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. The model is a hybrid technique that combines a Genetic Algorithm (GA) and a PSO algorithm. Each GA chromosome is an array encoding a meaning for updating the particles of the PSO algorithm. The evolved PSO algorithm is compared to a human-designed PSO algorithm by using ten artifi...

In this paper a particle swarm optimization (PSO) algorithm is presented to design a compact stepped triangle shape antenna in order to obtain the proper UWB bandwidth as defined by FCC. By changing the various cavity dimensions of the antenna, data to develop PSO program in MATLAB is achieved. The results obtained from the PSO algorithm are applied to the antenna design to fine-tune the bandwi...

-Aiming at the shortcoming of basic PSO algorithm, that is, easily trapping into local minimum, we propose an advanced PSO algorithm with SA and apply this new algorithm for solving TSP problem. The core of algorithm is based on the PSO algorithm. SA method is used to slow down the degeneration of the PSO swarm and increase the swarm’s diversity. The comparative experiments were made between PS...