Image segmentation is an important research issue in image processing. In this paper, hybridizing of the PSO and BBO algorithm for 2-D image segmentation is implemented. The common features from PSO and BBO algorithm are used and then hybridized for the segmentation. The results are evaluated on the basis of parameters; PSNR and SSIM. The results depicts that the proposed hybrid algorithm perfo...

Particle swarm optimization (PSO) algorithm is a kind of random optimization algorithm based on swarm intelligence. Swarm intelligence of PSO is produced by cooperation and competition between particles, which is used for guiding optimization search. PSO has been studied widely in many applications due to its good global searching ability. Currently PSO has been widely used in function optimiza...

Ant colonies behavior and their self-organizing capabilities have been popularly studied, and various swarm intelligence models and clustering algorithms also have been proposed. Unfortunately, the cluster number is often too high and convergence is also slow. We put forward a novel structure-attractor, which actively attracts and guides the ant’s behavior, and implement an efficient strategy t...

Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to various, mostly continuous, optimization problems. For all such heuristically guided search algorithms balance between exploitation and exploration is the determining factor for success. It is generally considered that in the ABC algorithm exploitation is performed by employed ...

nowadays using of new energies in the form of dispersed resources in the worlds is wide spreading. in this article we will design a dispersed production source in the form of a solar/wind hybrid power plant in order to supply the energy of a residential unit according to a sample load pattern. the aim of aforementioned design is to reduce its costs in a period of 20 years. in order to optimi...

K-medoids clustering algorithm is used to classify data, but the approach is sensitive to the initial selection of the centers and the divided cluster quality is not high. Basic Artificial Fish Swarm Algorithm is a new type of heuristic swarm intelligence algorithm, but optimization is difficult to get a very high precision due to the randomness of the artificial fish behavior. A novel clusteri...

This paper proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs Swarm Intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate respectively. The main contribution of this paper is to extend Swarm Intelligence algorithms to build a routing tree in such a way that ...

A novel approach of integrating two swarm intelligence algorithms is considered, one simulating the behaviour of birds flocking (Particle Swarm Optimisation) and the other one (Stochastic Diffusion Search) mimics the recruitment behaviour of one species of ants – Leptothorax acervorum. This hybrid algorithm is assisted by a biological mechanism inspired by the behaviour of blood flow and cells ...

A novel approach of integrating two swarm intelligence algorithms is considered, one simulating the behaviour of birds flocking (Particle Swarm Optimisation) and the other one (Stochastic Diffusion Search) mimics the recruitment behaviour of one species of ants – Leptothorax acervorum. This hybrid algorithm is assisted by a biological mechanism inspired by the behaviour of blood flow and cells ...

We show the emergence of Swarm Intelligence in physical robots. We transfer an optimization algorithm which is based on beeforaging behavior to a robotic swarm. In simulation this algorithm has already been shown to be more effective, scalable and adaptive than algorithms inspired by ant foraging. In addition to this advantage, bee-inspired foraging does not require (de-)centralized simulation ...