References

COMPARATIVE STUDY ON INTELLIGENT AND CLASSICAL MODELLING AND COMPOSITION OPTIMIZATION OF STEEL ALLOYS


[1] S. Ablameyko, L. Goras, M. Gori and V. Piuri, Neural Networks for Instrumentation, Measurement and Related Industrial Applications, V. Piuri (Eds.) NATO Science Series, IOS Press 185 (2003).

[2] M. F. Anjum, I. Tasadduq and K. Al-Sultan, Response surface methodology: A neural network approach, European Journal of Operational Research 101 (1997), 65-73.

[3] A. Cichoski and R. Unbehauen, Neural Networks for Optimization and Signal Processing, John Wiley & Sons, New York, 1993.

[4] G. Dini, A. Najafizadeh, S. M. Monir-Vaghefi and A. Ebnonnasir, Predicting of mechanical properties of Fe-Mn-(Al, Si) TRIP/TWIP steels using neural network modelling, J. Computational Materials Science 45 (2009), 959-965.

[5] P. Koprinkova and M. Petrova, Optimal control of batch biotechnological processes using neural network model, 9th Int. Conf. Systems for Automation of Engineering and Research, Sept. 24-26, Varna, Bulgaria, (1995), 95-99.

[6] P. Koprinkova-Hristova, M. Angelov, G. Kostov and P. Pandzharov, Neural network optimization of initial conditions of milk starter culture cultivation, Int. Symp. on Innovations in Intelligent Systems and Applications INISTA’2009, 29th June-1st July, Trabzon, Turkey, (2009) 32-36.

[7] S. Malinov, W. Sha and J. J. McKeown, Modelling and correlation between processing parameters and properties of titanium alloys using artificial neural network, J. Computational Materials Science 21 (2001), 375-394.

[8] S. Malinov and S. W. Sha, Software products for modelling and simulation in materials science, J. Computational Materials Science 28 (2003), 179-198.

[9] K. Miettinen, Nonlinear Multiobjective Optimization, Kluwer, Boston, 1999.

[10] H. Nakayama and Y. Sawaragi, Satisfying trade-off method for multiobjective programming, M. Grauer and A. P. Wierzbicki (Eds.), Interactive Decision Analysis, Springer-Verlag, LNEMS 229 (1984), 113-122.

[11] D. H. Nguyen and B. Widrow, Neural networks for self-learning control systems, Int. J. Control 54(6) (1991), 1439-1451.

[12] D. E. Rumelhart and J. L. McClelland, Parallel Distributed Processing, Vol. 1, MIT Press, Cambridge, MA, 1986.

[13] P. J. Werbos, Backpropagation through time: What it does and how to do it? Proceedings of the IEEE 78(10) (1990), 1550-1560.

[14] P. J. Werbos, An overview of neural networks for control, IEEE Control Systems (1991), 40-41.

[15] A. Wierzbicki, A mathematical basis for satisfying decision making, Mathematical Modelling 3(25) (1982), 391-405.

[16] A. Wierzbicki, On the completeness and constructiveness of parametric characterizations to vector optimization problems, OR Spektrum 8 (1986), 73-87.

[17] Hong-Seok Yang, Low-Carbon, Low-Temperature Bainite, Master Thesis, Graduate Institute of Ferrous Technology, Pohang University of Science and Technology, 2008.

[18] Hongliang Yi, -TRIP Steel, Department of Ferrous Technology, Thesis for Doctor of Philosophy, Graduate Institute of Ferrous Technology, Pohang University of Science and Technology, 2010.