Reactive power optimization is important to ensure power quality, improve system security, and reduce active power loss. So, this paper proposed parallel immune particle swarm optimization (PIPSO) algorithm. This algorithm makes basic particle swarm optimization (BPSO) and discrete particle swarm optimization (DPSO) to optimize in parallel, and improves the convergence capability of particle sw...

This paper presents a dynamic particle swarm optimization based search for optimal fusion configuration of sensors in distributed detection network in presence of a nonstationary binary symmetric channel. The wireless channel in sensor networks is a non-stationary random process, which moves the optima of the original problem, otherwise static. The optimal fusion configuration minimizes the pro...

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of...

In this paper, we incorporate pheromone courtship mode of biology to improve particle swarm optimizer. The particle swarm optimization technique has ever since turned out to be a competitor in the field of numerical optimization. A particle swarm optimization consists of a number of individuals refining their knowledge of the given search space. Particle swarm optimizations are inspired by part...

This study examines a variable-length Particle Swarm Algorithm for Social Programming. The Grammatical Swarm algorithm is a form of Social Programming as it uses Particle Swarm Optimisation, a social swarm algorithm, for the automatic generation of programs. This study extends earlier work on a fixed-length incarnation of Grammatical Swarm, where each individual particle represents choices of p...

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the varia...

In order to optimize the spectrum resource allocation in the orthogonal frequency division multiplexing system and minimize the transmitted power, this paper proposed a modified basic particle swarm optimization algorithm to allocate the subcarriers and bits of the orthogonal frequency division multiplexing system. The algorithm uses the average individual extreme value instead of individual ex...

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...

Cloud Computing is subscription-based service which is used to obtain storage space on network and computer resources. The cloud makes it possible to access information from anywhere at any time. Cloud provides both software and hardware necessary to run various applications according to the needs of the user. To fulfil those needs of user internet connection is required to access the cloud. In...

In this paper we theoretically investigate underlying assumptions that have been used for designing adaptive particle swarm optimization algorithms in the past years. We relate these assumptions to the movement patterns of particles controlled by coefficient values (inertia weight and acceleration coefficient) and introduce three factors, namely the autocorrelation of the particle positions, th...