PARTICLE SWARM OPTIMIZATION OF SOLAR CENTRAL RECEIVER SYSTEMS FROM A MONTE CARLO DIRECT MODEL

A mid-IR amplifier consisting of a tapered chalcogenide fiber coupled to an Er 3þ -doped chalcogenide microsphere has been optimized via a particle swarm optimization (PSO)

About the convergence of PSO, Van Den Bergh and Engelbrecht (2006) looked at the trajectories of the particles and proved that each particle converges to a stable point

In this paper, we proposed a new tracking framework based on Particle Swarm Optimization formalism and, demonstrated on both, synthetic and real data, that our algorithm outper-

Also upper and lower boundaries of solution space in each particle dimension are restricted based on properties of threats themselves in the field to avoid prema- turity In

In that way we have proposed a particular model which is a reactive multi-agent system (MAS) model called Logistic Multi-Agent System (LMAS) [5], because of the internal logistic

As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic

As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic

In this paper, a methodology for the design optimization of PVGCSs is presented intending to suggest the optimal values of the PVGCSs installation details such as