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Estimation of Difficult-to-Measure Process Variables Using Neural Networks - A comparison of simple MLP and RBF neural network properties


Slišković, Dražen; Nyarko, Emmanuel Karlo; Perić, Nedjeljko
Estimation of Difficult-to-Measure Process Variables Using Neural Networks - A comparison of simple MLP and RBF neural network properties // Proceedings of 12th IEEE Mediterranean Electrotechnical Conference, MELECON 2004
Zagreb, 2004. str. 387-390 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Estimation of Difficult-to-Measure Process Variables Using Neural Networks - A comparison of simple MLP and RBF neural network properties

Autori
Slišković, Dražen ; Nyarko, Emmanuel Karlo ; Perić, Nedjeljko

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

Izvornik
Proceedings of 12th IEEE Mediterranean Electrotechnical Conference, MELECON 2004 / - Zagreb, 2004, 387-390

Skup
The 12th IEEE Mediterranean Electrotechnical Conference, MELECON 2004

Mjesto i datum
Dubrovnik, Hrvatska, 12-15.05.2004.

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Difficult-to-measure process variable; estimation; soft-sensor; artificial neural networks

Sažetak
In this paper, two different artificial neural networks are tested and compared with regard to their application in the estimation of difficult- to-measure process variables. Two of the most commonly used neural networks, the MLP (multi- layer perceptron) and RBF (radial basis function) neural networks, with simple structure and standard training methods are chosen as examples. Neural network training is based on available data from a database of process variables measured over a long time period. The database in this paper is obtained using a simulation model of a real process. Without going deeper into theoretical background, relative properties of these neural networks are given through the results obtained by testing the trained networks and analysis performed on these results.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Temeljne tehničke znanosti



POVEZANOST RADA


Projekt / tema
0036017
0165103

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb,
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek