Prediction of flow stress for carbon steels using recurrent self-organizing neuro fuzzy networks

[1]  D. L. Baragar,et al.  The high temperature and high strain-rate behaviour of a plain carbon and an HSLA steel , 1987 .

[2]  Dana Ron,et al.  Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation , 1997, Neural Computation.

[3]  Peter Hodgson,et al.  The Application of Constitutive and Artificial Neural Network Models to Predict the Hot Strength of Steels , 1999 .

[4]  M. P. Phaniraj,et al.  The applicability of neural network model to predict flow stress for carbon steels , 2003 .

[5]  Prasad K. Yarlagadda,et al.  Neural network approach to flow stress evaluation in hot deformation , 1995 .

[6]  Alan K. Miller,et al.  Modelling the effects of recrystallization on the flow behavior during hot deformation by modifying an existing constitutive model I: Conceptual development of the MATMOD-ReX equations , 1989 .

[7]  Alan K. Miller,et al.  The influence of solutes on flow stress plateaus, with emphasis on back stresses and the development of unified constitutive equations , 1989 .

[8]  Peter Hodgson,et al.  The prediction of the hot strength in steels with an integrated phenomenological and artificial neural network model , 1999 .

[9]  T. Lowe.  Computer Simulation of Deformation Processing , 1988 .

[10]  Kamineni Pitcheswara Rao,et al.  Development of Constitutive Relationships Using Compression Testing of a Medium Carbon Steel , 1992 .

[11]  U. F. Kocks.  Laws for Work-Hardening and Low-Temperature Creep , 1976 .

[12]  Alan K. Miller,et al.  A simplified phenomenological model for non-elastic deformation: Predictions of pure aluminum behavior and incorporation of solute strengthening effects , 1978 .

[13]  Amit K. Ghosh.  A physically-based constitutive model for metal deformation , 1980 .

[14]  Sung-Kwun Oh,et al.  Self-organizing neurofuzzy networks based on evolutionary fuzzy granulation , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[15]  John G. Lenard,et al.  A comparative study of artificial neural networks for the prediction of constitutive behaviour of HSLA and carbon steels , 1996 .

[16]  R. W. Evans,et al.  Modelling flow stress evolution during elevated temperature deformation of two low carbon steels , 1996 .

[17]  N. Hatta,et al.  Modelling on flow stress of plain carbon steel at elevated temperatures , 1985 .

[18]  Yuri Estrin,et al.  A unified phenomenological description of work hardening and creep based on one-parameter models , 1984 .