Naslov
Analysis of neural network structures for modelling multiplicity of a chemical reactor

Autori
Kurtanjek, Želimir

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

Izvornik
Information Technology Interfaces 1998 / Cerić, V. - Zagreb : Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 1998, 537-543

Skup
Information Technology Interfaces 1998

Mjesto i datum
Pula, Hrvatska, 16.06.1998. - 19.06.1998

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
reactor multiplicity; neural network structure; NARMA models
(eactor multiplicity; neural network structure; NARMA models)

Sažetak
Neural network structures for modelling multiplicities in continuous chemical reactors are analysed. The following structures are investigated: 1) neural network auto regression with exogenous inputs NNARX, 2) neural network output model NNOE, 3) neural network autoregression moving averages with exogenous inputs with the error compensation of predictions NNARMAX1, 4) neural network autoregression moving averages with exogenous inputs NNARMAX2, 5) neural networks with state space innovations NNSSIF, 6) neural network with input output linearization NNIOL. The neural structures are investigated on computer simulation of patterns obtained from nonisothermal continuous reactor with an irreversible first order reaction. The neural network models are validated by statistical analysis of the residuals for two independent sets of trained and untrained patterns.

Izvorni jezik
Engleski

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