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The method of multivariate forecasting of economic processes based on a modified learning genetic algorithm
Kutakhov V.P., Filippov P.G., Vanyurikhin G.I., Korneenko V.P.
модифицированный обучающийся генетиче ский алгоритм LGAP (Learning Genetic Algorithm for Prognosis), позволяющий
Machine Learning and Genetic Algorithms
Golubev, A., Molchan, O.
Machine Learning and Genetic Algorithms
Formation of regression model for analysis of complex systems using methodology of genetic algorithms
Mokshin A.V., Mirziyarova D.A., Mokshin V.V.
of genetic (evolutionary) algorithms. The resulting regression models make it possible to predict the most
Comparative Analysis of Evolutionary Algorithms for the Problem of Parametric Optimization of PID Controllers
Konstantinov S.V., Baryshnikov A.A.
Six modern and promising evolutionary algorithms are described: genetic algorithm, differential
Intelligent Particle Swarm Optimization Using Q-Learning
Alvares P.A.
Intelligent Particle Swarm Optimization Using Q-Learning
Recent trends in cancer genomics and bioinformatics tools development
Anashkina A.A., Leberfarb E.Y., Orlov Y.L.
cancer prognosis
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
Novel GA-Based DNN Architecture for Identifying the Failure Mode with High Accuracy and Analyzing Its Effects on the System
Rezaeian N., Gurina R., Saltykova O.A., Hezla L., Nohurov M., Reza Kashyzadeh K.
architecture for all of them. To overcome this problem, a Genetic Algorithm (GA) was employed to find the best
The Parallel Genetic Algorithm for Construction of Technological Objects Neural Network Models
Tynchenko, Vadim Sergeevich, Petrovsky, Eduard Arkadievich, Tynchenko, Valeriya Valerievna
The parallel genetic algorithms implementation for neural networks models construction is discussed
Unsupervised Machine Learning Control Techniques for Solving the General Synthesis of Control System Problem
Nassrullah K.S., Stepanyan I.V., Nasrallah H.S., Florez N.J.M., Zidoun A.M., Mohammed S.R.
The focus of this study is a relatively new development in the field of control: machine learning

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