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A Stabilisation System Synthesis for Motion along a Preset Trajectory and Its Solution by Symbolic Regression that machine learning control by symbolic regression is used. In computational experiments, examples
Using symbolic regression techniques for machine learning to control robot movement: Advantages and consSymbolic regression techniques, a prominent facet of machine learning, have garnered attention
Расширенная задача оптимального управления и численный метод ее решения using evolutionary algorithms and symbol regression methods for structurally parametric optimization
Stabilisation System Synthesis for Motion along the Trajectory by Evolutionary Machine Learning Control function synthesis problem.Symbolic regression methods allow to find the mathematical expressions
Fuzzy regression analysis using trapezoidal fuzzy numbers© 2020 KIIE As a widely used method, regression analysis plays an increasingly important role
Problem of the Interpretability vs. Accuracy Trade-off in Symbolic Regression in robot motion: causes and solutionSymbolic regression holds promise in deciphering the underlying dynamics of robot motion, offering
Reinforcement Learning for Solving Control Problems in Robotics † of an object along a given trajectory, machine learning control by symbolic regression is used. An example
Integrative connection of mathematics and economics indicates the wide possibility of applying the methods and stages of the correlation and regression analysis
Piecewise Polynomial Models for Aggregation and Regression Analysis in Remote Sensing of the Earth Problems to
regression modeling. An important feature of study is demonstration of the way how represent the
aggregated
Complete Binary Variational Analytic Programming for Synthesis of Control at Dynamic Constraints, we use a new method of symbolic regression - a method of binary variational analytical programming
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