What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Algebra
Gleb Beliakov mainly investigates Fuzzy set, Fuzzy logic, Mathematical optimization, Artificial intelligence and Type-2 fuzzy sets and systems.
His Fuzzy set research includes elements of Discrete mathematics, Fuzzy control system, Algebra, Choquet integral and Linear programming.
His work carried out in the field of Choquet integral brings together such families of science as Ordered weighted averaging aggregation operator and Identification.
His Fuzzy logic research incorporates themes from Material implication, Mathematical economics, Decision support system and Unit interval.
His Decision support system research incorporates elements of Intelligent decision support system, Intranet, Source code and Knowledge-based systems.
His Artificial intelligence study combines topics in areas such as Value, Machine learning, Focus and Computer vision.
His most cited work include:
- Aggregation Functions: A Guide for Practitioners (1161 citations)
- Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice (326 citations)
- On averaging operators for Atanassov's intuitionistic fuzzy sets (220 citations)
What are the main themes of his work throughout his whole career to date?
Gleb Beliakov spends much of his time researching Mathematical optimization, Fuzzy logic, Fuzzy set, Artificial intelligence and Algorithm.
His Mathematical optimization study which covers Identification that intersects with Ordered weighted averaging aggregation operator.
The Fuzzy logic study combines topics in areas such as Measure and Focus.
His study looks at the intersection of Fuzzy set and topics like Discrete mathematics with Algebra, Operator, Lipschitz continuity, Theoretical computer science and Applied mathematics.
Gleb Beliakov interconnects Machine learning, Data mining, Computer vision and Pattern recognition in the investigation of issues within Artificial intelligence.
His Algorithm research is multidisciplinary, incorporating perspectives in Image reduction and Fuzzy control system.
He most often published in these fields:
- Mathematical optimization (26.35%)
- Fuzzy logic (21.62%)
- Fuzzy set (19.26%)
What were the highlights of his more recent work (between 2018-2021)?
- Fuzzy logic (21.62%)
- Mathematical optimization (26.35%)
- Choquet integral (8.78%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Fuzzy logic, Mathematical optimization, Choquet integral, Multiple-criteria decision analysis and Theoretical computer science.
His study on Fuzzy logic is covered under Artificial intelligence.
He usually deals with Mathematical optimization and limits it to topics linked to Decision problem and Axiom and Entropy.
Gleb Beliakov has researched Choquet integral in several fields, including Measure, Set, Outlier, Simplex and Operations research.
His Multiple-criteria decision analysis study incorporates themes from Linear programming, Matrix, Probabilistic logic and Pairwise comparison.
His research investigates the connection between Theoretical computer science and topics such as Representation that intersect with issues in Expression, Preference, Aggregate and Measure.
Between 2018 and 2021, his most popular works were:
- Learning fuzzy measures from data: Simplifications and optimisation strategies (21 citations)
- Nonmodularity index for capacity identifying with multiple criteria preference information (21 citations)
- Nonmodularity index for capacity identifying with multiple criteria preference information (21 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Algebra
Gleb Beliakov mainly focuses on Fuzzy logic, Linear programming, Mathematical optimization, Theoretical computer science and Index.
Fuzzy logic is a primary field of his research addressed under Artificial intelligence.
His studies in Mathematical optimization integrate themes in fields like Domain, Sugeno integral, Choquet integral and Curse of dimensionality.
Gleb Beliakov has included themes like Measure, Set, Construct, Constraint and Measure in his Choquet integral study.
He interconnects Monotonic function, Integer programming and Heuristic in the investigation of issues within Curse of dimensionality.
Gleb Beliakov combines subjects such as Preference, Expression and Aggregate with his study of Theoretical computer science.
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