Riyam Bassim Abdulmaged
Papers
1
Total Citations
28
H-Index
1
About
Riyam Bassim Abdulmaged is a rising researcher in industrial automation and intelligent control systems, whose work focuses on optimizing robotic arm-based conveyor belts (RACBs) for enhanced industrial efficiency. Her most-cited paper, published in 2024, introduces a novel hybrid control framework combining NARMA(L2)-FO(ANFIS)PD-I with the Jaya Optimization Algorithm to select and evaluate RACB motions. This work addresses critical challenges in robotic joint, motor, gear, and sequential movements, offering a computationally efficient solution that has already garnered 28 citations—a strong indicator of its relevance to scholars worldwide. Abdulmaged’s contributions lie at the intersection of soft computing, fractional-order control, and metaheuristic optimization, providing a systematic methodology for improving conveyor belt automation in resource-rich industrial sectors. Her research is particularly notable for its practical applicability, bridging theoretical advances in adaptive neuro-fuzzy inference systems (ANFIS) with real-world robotic arm deployment. As a researcher, she demonstrates a clear commitment to solving pressing industrial problems through intelligent algorithms, making her work valuable for students and engineers seeking to advance smart manufacturing and autonomous material handling systems.
Research Focus
Key Achievements
Top Papers
- 1