D.E. Kazaryan

Peoples' Friendship University of Russia, Dorodnitsyn Computing Centre

Papers

Total Citations

H-Index

About

D.E. Kazaryan is a researcher specializing in computational intelligence and control systems, with a particular focus on evolutionary algorithms and automated control synthesis. Their key research areas include grammatical evolution, genetic programming, and the network operator method for control system design. Kazaryan’s most notable contribution is the application of grammatical evolution—a branch of genetic programming that uses Backus-Naur form grammar specifications—to optimize neural networks for control system synthesis. This work, published in 2017, has garnered 9 citations and demonstrates how evolutionary algorithms can effectively generate symbolic expressions for complex control functions. Additionally, Kazaryan has advanced the field of identification control, addressing the challenge of controlling objects with unknown mathematical models. Their 2015 paper on the network operator method, cited 4 times, proposes a two-step approach: first solving the identification problem to model the object, then synthesizing a multi-dimensional control system. This work is particularly valuable for real-world applications where precise mathematical models are unavailable. Kazaryan’s research bridges evolutionary computation and control theory, offering practical solutions for automated system design.