Petri Neural Network Model for the Effect of Controlled Thermomechanical Process Parameters on the Mechanical Properties of HSLA Steels

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著者

    • DATTA S.
    • Department of Metallurgy, B. E. College(Deemed University)
    • SIL J.
    • Department of Computer Science and Technology

抄録

The effect of composition and controlled thermomechanical process parameters on the mechanical properties of HSLA steels is modelled using the Widrow-Hoff's concept of training a neural net with feed-forward topology by applying Rumelhart's back propagation type algorithm for supervised learning, using a Petri like net structure. The data used are from laboratory experiments as well as from the published literature. The results from the neural network are found to be consistent and in good agreement with the experimented results.

収録刊行物

  • ISIJ international  

    ISIJ international 39(10), 986-990, 1999-10 

    The Iron and Steel Institute of Japan

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