Naslov
Predicting the hardenability of steels using neural network

Autori
Filetin, Tomislav ; Majetić, Dubravko ; Žmak, Irena

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

Izvornik
Proceedings of the 7th International Scietific Conference Achivements in Mechanical & Materials Engineering / Dobrzanski, Leszek A. - Gliwice : Zakopane : Polish Academy of Sciences, 1998, 151-154

Skup
7 th International Scietific Conference Achivements in Mechanical & Materials Engineering

Mjesto i datum
Zakopane, Poljska ; Gliwice, Poljska, 29.11.1998. - 02.12.1998

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
hardenability of steels ; neural networks ; prediction

Sažetak
An attempt has been made to establish a non-linear statis discrete-time neuron model, teh so-called Static Elementary Preocessor (SEP). Based on the SEP neurons, a Static Multi layer Perceptron Neural Network is proposed to predict a Jominy hardness curve from chemical composition. To accelerate tge convergence of proposed static error-back propagation learning algorithm, the momentum method is applied. The learning results are presented in terms that are insensitive to the learning data range and allow easy comparison with other learning algorithms, independent of machine architecture or simulator implementation. In the learning process datasets with 121 heats are used - comprising samples from 40 steel grades with different chemical composition. The mean error between measured and predicted hardness data and standard deviation for testing dadtaset (60 heats - samples from 203 heats in question) is comparable with other published methods of prediction.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

POVEZANOST RADA