What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Machine learning
Artificial intelligence, Swarm intelligence, Algorithm, Firefly algorithm and Bat algorithm are his primary areas of study.
His Artificial intelligence research includes themes of Control parameters, Optimization problem and Cuckoo search.
His Swarm intelligence study combines topics in areas such as Parallel metaheuristic, Metaheuristic algorithms, Nature inspired, Evolutionary computation and Feature selection.
His study in Algorithm intersects with areas of studies such as Firefly protocol and Spacecraft.
To a larger extent, Iztok Fister studies Mathematical optimization with the aim of understanding Firefly algorithm.
His Bat algorithm study combines topics from a wide range of disciplines, such as Multimedia, Duration, Task and Benchmark.
His most cited work include:
- A comprehensive review of firefly algorithms (676 citations)
- A Brief Review of Nature-Inspired Algorithms for Optimization (295 citations)
- A review of chaos-based firefly algorithms (122 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Swarm intelligence, Algorithm, Differential evolution and Mathematical optimization.
Iztok Fister studied Artificial intelligence and Optimization problem that intersect with Heuristics.
His Swarm intelligence research is multidisciplinary, relying on both Computational intelligence, Cuckoo search, Metaheuristic, Artificial neural network and Swarm robotics.
Iztok Fister has included themes like Nature inspired and Representation in his Algorithm study.
His study looks at the intersection of Differential evolution and topics like Benchmark with Function.
He combines Firefly algorithm and Firefly protocol in his studies.
He most often published in these fields:
- Artificial intelligence (34.41%)
- Swarm intelligence (23.12%)
- Algorithm (18.28%)
What were the highlights of his more recent work (between 2019-2021)?
- Association rule learning (7.53%)
- Artificial intelligence (34.41%)
- Algorithm (18.28%)
In recent papers he was focusing on the following fields of study:
Iztok Fister focuses on Association rule learning, Artificial intelligence, Algorithm, Evolutionary algorithm and Differential evolution.
The various areas that Iztok Fister examines in his Artificial intelligence study include Machine learning and Optimization problem.
His studies in Bat algorithm and Swarm intelligence are all subfields of Algorithm research.
His Swarm intelligence research integrates issues from Swarm robotics and Engineering management.
His biological study spans a wide range of topics, including Population growth, Parallel algorithm and Global optimization.
His work investigates the relationship between Differential evolution and topics such as Particle swarm optimization that intersect with problems in Operations research and Development.
Between 2019 and 2021, his most popular works were:
- Bioinspired Computational Intelligence and Transportation Systems: A Long Road Ahead (25 citations)
- Post hoc analysis of sport performance with differential evolution (10 citations)
- A comprehensive database of Nature-Inspired Algorithms. (5 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
Iztok Fister mainly focuses on Association rule learning, Database transaction, Evolutionary algorithm, Differential evolution and Nature inspired.
His study in Association rule learning is interdisciplinary in nature, drawing from both Text mining and Data science.
His Database transaction research includes themes of Visualization and Optimization problem.
His Differential evolution research includes elements of Feature selection and Feature.
His Nature inspired research is multidisciplinary, incorporating perspectives in Evolutionary computation, Swarm intelligence and Bio inspired algorithms.
His Swarm intelligence research is classified as research in Algorithm.
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