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.
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.
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.
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.
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AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION
D Karaboga.
(2005)
A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
Dervis Karaboga;Bahriye Basturk.
Journal of Global Optimization (2007)
On the performance of artificial bee colony (ABC) algorithm
D. Karaboga;B. Basturk.
soft computing (2008)
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga;Bahriye Akay.
Applied Mathematics and Computation (2009)
A comprehensive survey: artificial bee colony (ABC) algorithm and applications
Dervis Karaboga;Beyza Gorkemli;Celal Ozturk;Nurhan Karaboga.
Artificial Intelligence Review (2014)
Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems
Dervis Karaboga;Bahriye Basturk.
soft computing (2007)
A modified Artificial Bee Colony algorithm for real-parameter optimization
Bahriye Akay;Dervis Karaboga.
Information Sciences (2012)
A novel clustering approach: Artificial Bee Colony (ABC) algorithm
Dervis Karaboga;Celal Ozturk.
soft computing (2011)
Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
D. T. Pham;D. Karaboga.
(2011)
A survey: algorithms simulating bee swarm intelligence
Dervis Karaboga;Bahriye Akay.
Artificial Intelligence Review (2009)
University of Birmingham
Victoria University of Wellington
Victoria University of Wellington
University of Maribor
Indian Institute of Information Technology Design and Manufacturing Jabalpur
Publications: 34
Profile was last updated on December 6th, 2021.
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