What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Algorithm
The scientist’s investigation covers issues in Artificial bee colony algorithm, Artificial intelligence, Swarm intelligence, Metaheuristic and Algorithm.
His Artificial bee colony algorithm research is multidisciplinary, incorporating perspectives in Optimization problem and Particle swarm optimization.
Artificial intelligence connects with themes related to Machine learning in his study.
Dervis Karaboga merges Swarm intelligence with Honey bee in his study.
Dervis Karaboga works mostly in the field of Metaheuristic, limiting it down to topics relating to Ant colony optimization algorithms and, in certain cases, Swarm robotics, as a part of the same area of interest.
His study looks at the intersection of Meta-optimization and topics like Multi-swarm optimization with Differential evolution and Evolutionary algorithm.
His most cited work include:
- A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm (4441 citations)
- AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION (3852 citations)
- On the performance of artificial bee colony (ABC) algorithm (2500 citations)
What are the main themes of his work throughout his whole career to date?
Dervis Karaboga spends much of his time researching Artificial bee colony algorithm, Artificial intelligence, Algorithm, Swarm intelligence and Mathematical optimization.
The Artificial bee colony algorithm study combines topics in areas such as Metaheuristic, Particle swarm optimization, Cluster analysis, Benchmark and Optimization problem.
Dervis Karaboga combines subjects such as Feature and Multi-swarm optimization with his study of Metaheuristic.
His Artificial intelligence research includes elements of Genetic algorithm, Machine learning and Pattern recognition.
His study in the field of Ant colony optimization algorithms, Tabu search, Ant colony and Parallel algorithm is also linked to topics like Wilcoxon signed-rank test.
Dervis Karaboga focuses mostly in the field of Swarm intelligence, narrowing it down to matters related to Bees algorithm and, in some cases, Meta-optimization.
He most often published in these fields:
- Artificial bee colony algorithm (61.29%)
- Artificial intelligence (54.03%)
- Algorithm (28.23%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial bee colony algorithm (61.29%)
- Artificial intelligence (54.03%)
- Optimization problem (25.00%)
In recent papers he was focusing on the following fields of study:
Dervis Karaboga focuses on Artificial bee colony algorithm, Artificial intelligence, Optimization problem, Machine learning and Computational intelligence.
His Artificial bee colony algorithm study contributes to a more complete understanding of Mathematical optimization.
His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Pattern recognition, with regards to Multi-objective optimization and Sorting.
His Optimization problem research is multidisciplinary, relying on both Swarm intelligence, Representation, Integer programming and Benchmark.
His Swarm intelligence research incorporates themes from Genetic algorithm, Optimization algorithm and Firefly algorithm.
In his research on the topic of Convolutional neural network, Metaheuristic is strongly related with Recurrent neural network.
Between 2017 and 2021, his most popular works were:
- Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey (126 citations)
- Pareto front feature selection based on artificial bee colony optimization (124 citations)
- Discovery of conserved regions in DNA sequences by Artificial Bee Colony (ABC) algorithm based methods (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Algorithm
Dervis Karaboga mostly deals with Artificial bee colony algorithm, Artificial intelligence, Machine learning, Benchmark and Computational intelligence.
Dervis Karaboga has researched Artificial bee colony algorithm in several fields, including Travelling salesman problem and Combinatorial optimization.
His Artificial intelligence study is mostly concerned with Evolutionary computation and Selection.
The various areas that Dervis Karaboga examines in his Benchmark study include Swarm intelligence, Optimization problem, Global optimization and Robustness.
Dervis Karaboga integrates Set and Algorithm in his studies.
His work carried out in the field of Algorithm brings together such families of science as Optimization algorithm, Convergence, Control parameters and Nonlinear system.
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.
