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THE MODIFIED GENETIC ALGORITHM WITH AUTOMATIC ADJUSTMENT
Zvonkov, V. B.
THE MODIFIED GENETIC ALGORITHM WITH AUTOMATIC ADJUSTMENT
Adaptive genetic algorithms used to analyze behavior of complex system
Mokshin A., Mokshin V., Sharnin L.
of this regression model is constructed on the basis of the genetic algorithms technique. This allows us to predict a
MULTI-POPULATION GENETIC ALGORITHM FOR CRYSTAL STRUCTURES SOLUTION FROM X-RAY POWDER DIFFRACTION DATA
Aleksandr, Zaloga, Якимов, И., Petr, Dubinin
using the multi-population genetic algorithm (MPGA). The MPGA convergence charts and the atomic
Self-configuring Nature Inspired Algorithms for Combinatorial Optimization Problems
Semenkina, Olga Ev., Popov, Eugene A., Semenkina, Olga Er., Семенкина, Ольга Е., Попов, Евгений А., Семенкина, Ольга Э.
In this work authors introduce and study the self-configuring Genetic Algorithm (GA) and the self
Dynamic features selection in authorship identification problem
Paramonov, A. I., Trukhanovich, I. A., Kuntsevich, U., Парамонов, А. И., Труханович, И. А., Кунцевич, В. С.
of defining features by genetic algorithm.
Application of Self-Gonfiguring Genetic Algorithm for Human Resource Management
ˇSkraba, Andrej, Kofjaˇc, Davorin, ˇZnidarˇsiˇc, Anja, Maletiˇ, Matjaˇz, Rozman, ˇCrtomir, Semenkina, Maria E., Semenkin, Eugene S., Stanovov, Vladimir V., Шкраба, Андрей, Кофьяч, Даворин, Жнидаршич, Аня, Малетич, Матьяж, Рoзман, Чртомир, Семенкин, Евгений С., Семенкина, Мария Е., Становов, Владимир В.
this prob- lem, a self-configuring genetic algorithm is applied with several constraint handling methods
USING DETERMINISTIC GENETIC ALGORITHM TO PROVIDE SECURED CRYPTOSYSTEM
Alhussain A.H., Stefanuk V.L.
This paper gives an example of applying deterministic genetic algorithm in symmetric encryption
The bases of weighted graphs
Alpin J., Mubarakzianow R.
an equivalence class. One can define an order on the set of graphs in the natural way. It is shown that any
Cooperation of Bio-inspired and Evolutionary Algorithms for Neural Network Design
Akhmedova, Shakhnaz A., Stanovov, Vladimir V., Semenkin, Eugene S., Ахмедова, Шахназ А., Становов, Владимир В., Семенкин, Евгений С.
, as well as a new algorithm based on the cooperation of Differential Evolution and Particle Swarm Optimiza
METHOD OF BINARY ANALYTIC PROGRAMMING TO LOOK FOR OPTIMAL MATHEMATICAL EXPRESSION
Diveev A.I., Lomakova E.M.
algorithm, there is a problem of crossover. Genetic programming performs a crossover only in certainpoints

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