What is he best known for?
The fields of study he is best known for:
- Control theory
- Algorithm
- Genetic algorithm
His primary areas of study are Electric power system, Algorithm, Control theory, Genetic algorithm and Sizing.
In Electric power system, Ehab S. Ali works on issues like Capacitor, which are connected to Thyristor.
Ehab S. Ali has researched Control theory in several fields, including Control engineering, Optimization problem and Particle swarm optimization.
His Optimization problem study incorporates themes from Metaheuristic, Robustness and Search algorithm.
Ehab S. Ali combines subjects such as Time domain, PID controller and Automatic frequency control with his study of Genetic algorithm.
His study in Sizing intersects with areas of studies such as Sensitivity, Photovoltaic system, Turbine and Distributed generation.
His most cited work include:
- Bacteria foraging optimization algorithm based load frequency controller for interconnected power system (291 citations)
- BFOA based design of PID controller for two area Load Frequency Control with nonlinearities (153 citations)
- Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations (135 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Control theory, Electric power system, Algorithm, Control theory and Genetic algorithm.
His Control theory study integrates concerns from other disciplines, such as Optimization problem and Particle swarm optimization.
Within one scientific family, he focuses on topics pertaining to Capacitor under Electric power system, and may sometimes address concerns connected to Thyristor.
In his work, Heuristic is strongly intertwined with Stability, which is a subfield of Control theory.
His study in Genetic algorithm is interdisciplinary in nature, drawing from both Automatic frequency control and Cuckoo search.
Ehab S. Ali focuses mostly in the field of PID controller, narrowing it down to topics relating to Bat algorithm and, in certain cases, Search algorithm and Simulated annealing.
He most often published in these fields:
- Control theory (79.37%)
- Electric power system (58.73%)
- Algorithm (46.03%)
What were the highlights of his more recent work (between 2018-2020)?
- Whale (7.94%)
- Operations research (6.35%)
- Total cost (11.11%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Whale, Operations research, Total cost, Variable and Minification.
Total cost combines with fields such as Control reconfiguration and Differential evolution in his work.
Between 2018 and 2020, his most popular works were:
- Optimal network restructure via improved whale optimization approach (2 citations)
- Optimal network restructure via improved whale optimization approach (2 citations)
- Improved Whale Optimization Algorithm for Optimal Network Reconfiguration (0 citations)
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
