Pregled bibliografske jedinice broj: 768889
Neural Network Prediction of Signal Strength for Irregular Indoor Environments
Neural Network Prediction of Signal Strength for Irregular Indoor Environments // Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije, 56 (2015), 1; 55-68 doi:10.7305/automatika.2015.04.463 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 768889 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Neural Network Prediction of Signal Strength for Irregular Indoor Environments
(Neural Network Prediction of Signal Strength for Irregular Environments)
Autori
Vilović, Ivan ; Burum, Nikša
Izvornik
Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije (0005-1144) 56
(2015), 1;
55-68
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Indoor propagation ; complex indoor environment ; signal strength prediction ; neural network modelling ; ray tracing ; Motley-Keenan method ; optimal position
Sažetak
A neural-network based approach for modelling propagation inside complex indoor environments is presented. Selection of the neural network model, initialization, and training and performance evaluation are studied in details. Furthermore, in order to determine optimal access point arrangement the neural network propagation model is merged with the particle swarm optimization method. In the case of simple indoor environments the developed propagation model is equally accurate as the deterministic methods, while in the case of complex environments the proposed method shows superior properties. Finally, the calculated results were tested in direct comparison with the measurements for both simple and complex indoor environments.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
MZO-ZP-275-0000000-3260 - Integralna kvaliteta usluge komunikacijskih i informacijskih sustava (Lipovac, Vladimir, MZO ) ( CroRIS)
Ustanove:
Sveučilište u Dubrovniku
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus