Abstract

A method for systems identification using artificial intelligence is presented in this paper. To prove its usefulness applicability, it was verified in the health sector in the clarification of electrophoresis tests, but this application can be implemented in different areas of interest e.g. in business, management, advertising, etc. A wide examination has been done developing the hearty assets of genetic algorithms and proving their abilities across a large range of glitches. We can use this application in many events areas (medical, business, etc.) The resulting references may constitute the basis of future work in the use of genetic algorithms in the business area.

References

1. C. Săvulescu, I. Sima, E. Sofron, “The functional identification of systems using genetic algorithms”, Proceedings of the 1st International Symposium on Electrical and Electronics Engineering, pp. 82-85, ISBN 973-627-355-3, Galaţi 12-13 October 2006J
2. A.T.Andrews, – Theory, Techniques and Biotechnical and Clinical Applications, Oxford University Press, 1993. [3] Al. Ene, C. Savulescu, “Sisteme cu inteligenta artificiala”, Indrumar de laborator, Pitesti, 1998.
3. Al. Ene, C. Savulescu, “Sisteme cu inteligenta artificiala”, Indrumar de laborator, Pitesti, 1998.
4. [Online] Available: https://www.quora.com/How-can-I-run-simulations-using-genetic-algorithms-in-non-science-fields-e- g-design-or-business, access date 2017-04-09.
5. [Online] Available: http://www.rp.pl/Biznes-IT/309209922-Sztuczna-inteligencja-przyszloscia-nowoczesnego- biznesu.html#ap-1, access date 2017-04-07.
6. [Online] Available: http://zeszyty- naukowe.wwsi.edu.pl zeszyty/zeszyt1/Algorytmy_Ewolucyjne_I_Ich_Zastosowania. pdf, access date 2017-04-05.

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