Access Point Selection Using Particle Swarm Optimization in Indoor Positioning Systems

2018 ◽  
Author(s):  
Ahmed K. Abed ◽  
Ikhlas Abdel-Qader
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Access Point ◽  
Indoor Positioning ◽  
Point Selection ◽  
Swarm Optimization ◽  
Positioning Systems

An Improved Particle Swarm Optimization for Indoor Positioning

2011 ◽  
pp. 501-509
Author(s):  
Hui Zhu
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Nonlinear Optimization ◽  
Social System ◽  
Particle Swarm ◽  
Taylor Series Expansion ◽  
Pso Algorithm ◽  
Indoor Positioning ◽  
Swarm Optimization ◽  
Fish Schooling

Particle Swarm Optimization (PSO) is a newly appeared technique for evolutionary computation. It was originated as a simulation for a simplified social system such as the behavior of bird flocking or fish schooling. An improved PSO algorithm (IPSO) is introduced to solve the nonlinear optimization for indoor positioning. The algorithm achieves the optimal coordinates through iterative searching. Compared with standard PSO algorithm, the algorithm converges faster and can find the global best position. The error of position estimated by this algorithm is smaller than that estimated in Taylor Series Expansion (TSE) and Genetic Algorithm (GA). Thus this algorithm is proven to be a fast and effective method in solving nonlinear optimization for indoor positioning.

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