G.I. Balandina
Papers
2
Total Citations
34
H-Index
2
About
G.I. Balandina is a researcher in computational intelligence and control systems, with a primary focus on evolutionary algorithms, symbolic regression, and optimal control for mobile robotics. Her work bridges the gap between theoretical algorithm design and practical robotic applications. Balandina’s most cited paper (2019, 27 citations) provides a rigorous comparative analysis of random search and evolutionary algorithms for the optimal control of mobile robots, offering experimental insights into their relative performance on a simulated robot model. This study has become a reference point for researchers selecting optimization methods in robotics. She is also the developer of a novel numerical symbolic regression method called complete binary variational genetic programming (2017, 7 citations), which improves upon traditional genetic programming by enhancing crossover efficiency, reducing the search space, and accelerating the optimization process for control system synthesis. This contribution demonstrates her ability to innovate algorithmic techniques that directly address computational bottlenecks. Balandina’s work is particularly valuable for students and researchers exploring evolutionary computation, control theory, and autonomous systems, as it provides both foundational comparisons and novel methodological advances in the field.
Research Focus
Key Achievements
Top Papers
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