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.

Askhat I Diveev
Federal Research Center “Computer Science and Control” of RAS; Engineering Academy Peoples’ Friendship University of Russia Vavilov str., 44, Moscow, Russia, 119333; Miklukho-Maklaya str., 6, Moscow, Russia, 117198

Doctor of technical sciences, professor, chief of sector of Cybernetic problems, professor of department Mechanics and mechatronics

Evgenia M Lomakova
Engineering Academy Peoples’ Friendship University of Russia Miklukho-Maklaya str., 6, Moscow, Russia, 117198

graduate student, department Mechanics and mechatronics

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