Naslov
Using Particle Swarm Optimization in Training Neural Network for Indoor Field Strength Prediction

Autori
Vilović, Ivan ; Burum, Nikša ; Milić, Đorđe

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
PROCEEDINGS ELMAR-2009 / Grgić, Mislav ; Božek, Jelena ; Grgić, Sonja - Zadar : Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2009, 275-278

ISBN
978-953-7044-10-7

Skup
51st International Symposium ELMAR-2009

Mjesto i datum
Zadar, Hrvatska, 28.09.2009. - 30.09.2009

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neural network; Multilayer perceptron; Training algorithm; Backpropagation algorithm; Gradient descent algorithm; Levenberg-Marquardt algorithm; Particle swarm optimization

Sažetak
This paper presents a comparison of results obtained from neural network training by backpropagation and particle swarm optimization (PSO) algorithms. The neural network model has been developed for field strength prediction in indoor environments. It has been already shown for neural networks as powerful tool in RF propagation prediction. It is very important to choose proper algorithm for training a neural network, so we compared BP training algorithms: gradient descent method and Levenberg- Marquardt algorithm with PSO algorithm. PSO algorithm has been shown as powerful method for global optimization in several applications. A floor of university building in Dubrovnik has been used as case for simulation and measurement of signal strength. The results show that the neural network weights converge faster with PSO than with standard BP algorithms.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

POVEZANOST RADA