The Neural Network That Can Find the Maximum Income of Refinery

Abstract

In this article we are going to introduce the neural network approach to approximate the solution for optimization problems. Using this approach we are able to approximate the optimum values for the large class of functions in particular giving the prices of different products that are resulted from refining the crude petroleum into different substances. We are going to design a neural network that can provide us with a decomposition of the given crude petroleum into resulted products in such a way that is most beneficial for the refinery.

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Mashood, B. and Milbank, G. (2014) The Neural Network That Can Find the Maximum Income of Refinery. Open Journal of Optimization, 3, 13-18. doi: 10.4236/ojop.2014.32002.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Hetz, J., Krough, A., Hetz, R.P.J., Krough, A. and Palmer, R. (1991) Introduction to the Theory of Neural Computation. Copy Right C, Addison Wesley Company.
[2] Haykin, S. (1999) Neural Networks A Comprehensive Foundation. 2nd Edition, Prentice Hall. Inc.
[3] Gass, I. (1958) Linear Programming. McGraw Hill, New York.
[4] Minc, H. (1988) Nonnegative Matrices. John Wiley and Sons. New York.

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