PSO and ACO Algorithms Applied to Location Optimization of the WLAN Base Station (CROSBI ID 530356)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Vilović, Ivan ; Burum, Nikša ; Šipuš, Zvonimir ; Nađ, Robert
engleski
PSO and ACO Algorithms Applied to Location Optimization of the WLAN Base Station
The main goal of this work is to show the use of evolutionary computation techniques The Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) in indoor propagation problem. These algorithms employ different strategies and computational efforts, but also they have something in common. Therefore, it is appropriate to compare their performance with the Genetic algorithm (GA). We have demonstrated their ability to optimize base station location using data from neural network model of Wireless Local Area Network (WLAN). The results show that PSO has better properties compared to ACO algorithm. The ACO algorithm needs further work to optimize the algorithm parameters, improve analysis of pheromone data and reduce computation time. However, the ant colony based approach is utilizable for solving such problems.
particle swarm optimization; ant colony optimization; genetic algorithms; antenna location optimization
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Podaci o prilogu
361-364-x.
2007.
objavljeno
Podaci o matičnoj publikaciji
Bonefačić, Davor
Zagreb: Hrvatsko društvo za komunikacije, računarstvo, elektroniku, mjerenja I automatiku (KoREMA)
978-953-6037-50-6
Podaci o skupu
19th International Conference on Applied Electromagnetics and Communications
predavanje
24.09.2007-26.09.2007
Dubrovnik, Hrvatska