engleski

Application of Neural Networks in Predicting the Steel Properties

The purpose of this paper is to demonstrate how a neural network is used for predicting steel properties when some of the relevant influence factors and their relations are unknown. An attempt has been made to establish a non-linear static discrete-time neuron model, the so-called Static Elementary Processor (SEP). Based on SEP neurons, a static multi layer forward neural network is proposed to predict the Jominy Hardness curve from chemical composition. The same method has been used in predicting the tempering curve from chemical composition and austenizing temperature of tool steels. The mean error between hardness data fromm catalogue and predicted hardness data, and standard deviation for testing dataset are small and acceptable in both studies.

steels; artificial neural network; predicting of properties; Jominy curve; tempering curve

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