What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Machine learning
His primary scientific interests are in Mathematical optimization, Metaheuristic, Heuristics, Artificial intelligence and Hyper-heuristic.
Mathematical optimization is closely attributed to Benchmark in his study.
Ender Özcan interconnects Memetic algorithm, Particle swarm optimization, Multi-swarm optimization and Reinforcement learning in the investigation of issues within Metaheuristic.
His research integrates issues of Machine learning and Pattern recognition in his study of Artificial intelligence.
His work in Local search tackles topics such as Tabu search which are related to areas like Adaptation.
His studies deal with areas such as Beam search, Incremental heuristic search, Set and Selection as well as Heuristic.
His most cited work include:
- Hyper-heuristics: a survey of the state of the art (703 citations)
- A Classification of Hyper-heuristic Approaches (364 citations)
- Particle swarm optimization: surfing the waves (352 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Heuristics, Mathematical optimization, Artificial intelligence, Heuristic and Hyper-heuristic.
His Heuristics research integrates issues from Domain, Set, Selection, Problem domain and Benchmark.
All of his Mathematical optimization and Metaheuristic, Local search, Memetic algorithm, Genetic algorithm and Heuristic investigations are sub-components of the entire Mathematical optimization study.
Ender Özcan has included themes like Optimization problem and Particle swarm optimization in his Metaheuristic study.
His Artificial intelligence research includes themes of Machine learning and Pattern recognition.
As a member of one scientific family, Ender Özcan mostly works in the field of Heuristic, focusing on Bin packing problem and, on occasion, Representation.
He most often published in these fields:
- Heuristics (46.96%)
- Mathematical optimization (44.75%)
- Artificial intelligence (33.15%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (33.15%)
- Mathematical optimization (44.75%)
- Heuristic (33.15%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Mathematical optimization, Heuristic, Heuristics and Metaheuristic.
His biological study spans a wide range of topics, including Class and Machine learning, Dropout.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Composite number and Stiffness.
His Heuristic research includes elements of No free lunch theorem, Set, Selection and Theory of computation.
The Heuristics study combines topics in areas such as Domain, Artificial neural network and Domain knowledge.
The concepts of his Metaheuristic study are interwoven with issues in Field, Local search and Management science.
Between 2017 and 2021, his most popular works were:
- A Classification of Hyper-Heuristic Approaches: Revisited (36 citations)
- Recent Advances in Selection Hyper-heuristics (33 citations)
- Evolutionary computation for wind farm layout optimization (24 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Algorithm
His main research concerns Machine learning, Artificial intelligence, Operations research, Hyper-heuristic and Heuristic.
His work on Computational intelligence is typically connected to Self as part of general Machine learning study, connecting several disciplines of science.
His Hyper-heuristic study spans across into areas like Development, Set, Learning automata and Multi-objective optimization.
Learning automata is intertwined with Metaheuristic, Problem domain, Mathematical optimization, Evolutionary computation and Optimization problem in his research.
The study incorporates disciplines such as Java, MATLAB, Evaluation function and Python in addition to Evolutionary computation.
Ender Özcan has researched Heuristic in several fields, including Class, Heuristics and Selection.
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