Zahra Rohani
Papers
2
Total Citations
8
H-Index
2
About
Zahra Rohani is a researcher specializing in artificial intelligence, with a focus on path planning, optimization algorithms, and fuzzy logic systems. Her most notable contribution is the development of a hybrid approach that integrates the Simplified Memory Bounded A* (SMA*) search algorithm with Particle Swarm Optimization (PSO), enhanced by fuzzy logic to improve cooperation between the two methods. This work, published in 2020, addresses the critical challenge of efficient path planning in complex environments, a key problem in AI and robotics. By combining SMA*’s memory-efficient search with PSO’s global optimization capabilities, Rohani’s method achieves superior performance in navigating dynamic spaces. Her research has garnered attention, with her top-cited paper accumulating 6 citations, reflecting its relevance to scholars working on intelligent navigation systems. Rohani’s work stands out for its practical application in autonomous systems, offering a scalable solution for real-world path planning tasks. Her contributions underscore the potential of hybrid AI techniques to solve computationally intensive problems, making her a promising voice in the field of optimization and search algorithms.
Research Focus
Key Achievements
Top Papers
- 1
- 2