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Effects of Inertia and Acceleration Coefficients on Particle Swarm Optimization Algorithm for Selection in the Swarm of Satellites

Abstract

Tahir Rehman and Faizullah Khan

PSO is getting some serious attention in recent era in optimization problem. It reduces the computational efforts and memory load. It is the artificial intelligence which is inspired by the social movement of elements in a group, for example birds flock or fish school etc. Optimization techniques are stochastic, deterministic, random and probabilistic. Stochastic technique is used where the information about the search space is not exactly known. Inertia weight is a major parameter which ominously effects the union, manipulation and exploration trade of in PSO technique. This article deals with the effect of the inertia and acceleration coefficients on the selection of a satellite that obeys the PSO algorithm.

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