Hasan Cana
Papers
1
Total Citations
4
H-Index
1
About
Hasan Cana’s research lies at the intersection of robotics, neural networks, and evolutionary optimization, with a focus on intelligent control systems. His most cited work, “Robotic Arm Control With Neural Networks Using Genetic Algorithm Optimization Approach” (2014), introduces a novel method that employs structural genetic algorithms to optimize neural network parameters for precise control of robotic arm joint movements. By modeling the arm in 3D and simulating it in real-time using MATLAB, Cana demonstrated that neural networks offer a simple yet highly effective solution for robotic control tasks. This contribution has garnered 4 citations, reflecting its relevance in the fields of automation and artificial intelligence. Cana’s work is notable for bridging the gap between bio-inspired optimization techniques and practical robotic applications, offering a foundation for further research in adaptive control systems. His approach underscores the potential of combining evolutionary algorithms with neural networks to enhance the efficiency and accuracy of robotic manipulators, making his research a valuable reference for students and engineers exploring intelligent robotics and control theory.
Research Focus
Key Achievements
Top Papers
- 1