hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.7305/automatika.2014.12.556

Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms

Ivan Vilović   ORCID icon orcid.org/0000-0001-7578-758X ; Department of Electrical Engineering and Computing University of Dubrovnik, Dubrovnik, Croatia
Nikša Burum   ORCID icon orcid.org/0000-0002-1197-0235 ; Department of Electrical Engineering and Computing University of Dubrovnik, Dubrovnik, Croatia

Puni tekst: engleski, pdf (2 MB) str. 317-329 preuzimanja: 462* citiraj
APA 6th Edition
Vilović, I. i Burum, N. (2014). Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms. Automatika, 55 (3), 317-329. https://doi.org/10.7305/automatika.2014.12.556
MLA 8th Edition
Vilović, Ivan i Nikša Burum. "Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms." Automatika, vol. 55, br. 3, 2014, str. 317-329. https://doi.org/10.7305/automatika.2014.12.556. Citirano 24.10.2020.
Chicago 17th Edition
Vilović, Ivan i Nikša Burum. "Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms." Automatika 55, br. 3 (2014): 317-329. https://doi.org/10.7305/automatika.2014.12.556
Harvard
Vilović, I., i Burum, N. (2014). 'Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms', Automatika, 55(3), str. 317-329. https://doi.org/10.7305/automatika.2014.12.556
Vancouver
Vilović I, Burum N. Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms. Automatika [Internet]. 2014 [pristupljeno 24.10.2020.];55(3):317-329. https://doi.org/10.7305/automatika.2014.12.556
IEEE
I. Vilović i N. Burum, "Location Optimization of WLAN Access Points Based on a Neural Network Model and Evolutionary Algorithms", Automatika, vol.55, br. 3, str. 317-329, 2014. [Online]. https://doi.org/10.7305/automatika.2014.12.556

Sažetak
In this article we intend to show the use of well-known evolutionary computation techniques - Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) - in an indoor propagation problem. Although these algorithms employ different strategies and computational efforts, they also share certain similarities. Their performance is compared with a genetic algorithm (GA), which is used as reference in this case. The ability of these algorithms to optimize access point locations using data derived from the neural network model of a particular Wireless Local Area Network (WLAN) is demonstrated. Better results are obtained by the PSO algorithm compared to the ACO algorithm. Although the ACO algorithm requires further work to optimize its parameters, improve the analysis of pheromone data and reduce computation time, the ant colony-based approach is useful for solving propagation problems.

Ključne riječi
Indoor propagation; Complex indoor environment; Signal strength prediction; WLAN; Neural network modelling; Access point optimization; Particle swarm optimization; Ant colony optimization

Hrčak ID: 133167

URI
https://hrcak.srce.hr/133167

[hrvatski]

Posjeta: 721 *