Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire popu...

(Background) To solve the cluster analysis better, we propose a new method based on chaotic particle swarm optimization (CPSO) algorithm.
 (Methods) In order to enhance performance in clustering, novel CPSO. We first evaluate clustering of this model using Variance Ratio Criterion (VRC) as evaluation metric. The effectiveness CPSO algorithm is compared with that traditional Particle Swarm ...

Among variety of meta-heuristic population-based search algorithms, particle swarm optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile optimization tool, which incorporates the experience of the whole swarm into the movement of particles. Although the exploitation ability of this algorithm is great, it cannot comprehensively explore the search space and may ...

Abstract: In existing forecasting research papers support vector regression with chaotic mapping function and evolutionary algorithms have shown their advantages in terms of forecasting accuracy improvement. However, for classical particle swarm optimization (PSO) algorithms, trapping in local optima results in an earlier standstill of the particles and lost activities, thus, its core drawback ...

The losses in electrical power systems are a great problem. Multiple methods have been utilized to decrease transmission lines. proper adjusting of reactive resources is one way minimize the any system. Reactive Power Optimization (RPO) problem nonlinear and complex optimization contains equality inequality constraints. RPO highly essential operation control systems. Therefore, study concentrat...

Swarm Intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment causing coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. Thi...

This paper introduces hybridization of particle swarm optimization (PSO) with genetic algorithm (GA) denoted as PSO+GA provides an efficient approach which is used to solve non linear chaotic datasets. The proposed algorithm employed in probabilistic neural network(PNN) which is a variant of radial basic function artificial neural network (RBFANN) for finding precise value spread factor for acc...