METHOD OF BINARY ANALYTIC PROGRAMMING TO LOOK FOR OPTIMAL MATHEMATICAL EXPRESSION
- Authors: Diveev A.I1,2, Lomakova E.M2
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Affiliations:
- Federal Research Center “Computer Science and Control” of RAS
- Engineering Academy Peoples’ Friendship University of Russia
- Issue: Vol 18, No 1 (2017)
- Pages: 125-134
- Section: CYBERNETICS AND MECHATRONICS
- URL: https://ogarev-online.ru/2312-8143/article/view/335330
- DOI: https://doi.org/10.22363/2312-8143-2017-18-1-125-134
- ID: 335330
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Abstract
In the known methods of symbolical regression by search of the solution with the help of a genetic algorithm, there is a problem of crossover. Genetic programming performs a crossover only in certainpoints. Grammatical evolution often corrects a code after a crossover. Other methods of symbolical regression use excess elements in a code for elimination of this shortcoming. The work presents a new method of symbolic regression on base of binary computing trees. The method has no problems with a crossover. Method use a coding in the form of a set of integer numbers like analytic programming. The work describes the new method and some examples of codding for mathematical expressions.
About the authors
Askhat I Diveev
Federal Research Center “Computer Science and Control” of RAS; Engineering Academy Peoples’ Friendship University of Russia
Email: aidiveev@mail.ru
Doctor of technical sciences, professor, chief of sector of Cybernetic problems, professor of department Mechanics and mechatronics Vavilov str., 44, Moscow, Russia, 119333; Miklukho-Maklaya str., 6, Moscow, Russia, 117198
Evgenia M Lomakova
Engineering Academy Peoples’ Friendship University of Russia
Email: lomakovajm@gmail.com
graduate student, department Mechanics and mechatronics Miklukho-Maklaya str., 6, Moscow, Russia, 117198
References
- Koza, J.R. Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, Massachusetts, London, MA: MIT Press, 1992. 819 p.
- O’Neill, M., Ryan, C. Grammatical Evolution. IEEE Trans. Evol. Comput. 2001, 5. Pp. 349-358.
- Zelinka, I. Analytic programming by Means of SOMA Algorithm. In Proceedings of 8th InternationalConference on Soft Computing Mendel 02, 2002, Brno, Czech Republic. Pp. 93-101.
- Diveev, A., Sofronova, E. Application of Network Operator Method for Synthesis of Optimal Structure and Parameters of Automatic Control System. Proc. of 17-th IFAC World Congress, Seoul, 05.07.2008 - 12.07.2008. Pp. 6106-6113.
- Miller, J., Thomson, P. Cartesian Genetic Programming. Proc. EuroGP’2000R 3rd European Conf. Genetic Programming, R. Poli, W. Banzhaf, W.B. Langdon, J.F. Miller, P. Nordin, and Fogarty, T.C. Eds., Edinburgh, Scotland, 2000, vol. 1802. Berlin: Springer-Verlag. Pp. 121-132.
- Luo, C., Zhang, S.-L. Engineering Applications of Arti cial Intelligence. 2012, 25. Pp. 1182-1193.
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