What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Algorithm
His primary areas of investigation include Fuzzy set, Fuzzy logic, Fuzzy set operations, Artificial intelligence and Defuzzification.
His Fuzzy set research integrates issues from Algorithm, Type and Data mining, Aggregate.
His Fuzzy logic research focuses on Computational complexity theory and how it connects with Series and Representation theorem.
Artificial intelligence is often connected to Machine learning in his work.
His Defuzzification study integrates concerns from other disciplines, such as Fuzzy classification, Type-2 fuzzy sets and systems and Membership function.
The study incorporates disciplines such as Fuzzy number and Neuro-fuzzy in addition to Fuzzy classification.
His most cited work include:
- Type-2 fuzzy sets made simple (1942 citations)
- Interval Type-2 Fuzzy Logic Systems Made Simple (1418 citations)
- Geometric Type-1 and Type-2 Fuzzy Logic Systems (265 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Fuzzy set, Fuzzy logic, Artificial intelligence, Defuzzification and Fuzzy set operations.
His Fuzzy set research incorporates themes from Algorithm, Theoretical computer science, Data mining and Interval.
He has researched Fuzzy logic in several fields, including Mathematical optimization, Series and Control theory.
Robert John works mostly in the field of Artificial intelligence, limiting it down to topics relating to Machine learning and, in certain cases, Contextual image classification.
Robert John has included themes like Fuzzy mathematics, Fuzzy classification, Fuzzy associative matrix and Membership function in his Defuzzification study.
His research investigates the connection between Fuzzy set operations and topics such as Neuro-fuzzy that intersect with issues in Fuzzy rule.
He most often published in these fields:
- Fuzzy set (51.57%)
- Fuzzy logic (45.29%)
- Artificial intelligence (36.32%)
What were the highlights of his more recent work (between 2018-2021)?
- Fuzzy logic (45.29%)
- Fuzzy set (51.57%)
- Fuzzy control system (17.49%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Fuzzy logic, Fuzzy set, Fuzzy control system, Interval and Mathematical optimization.
His study in Fuzzy logic is interdisciplinary in nature, drawing from both Machine learning, Monotonic function and Data mining.
In the field of Fuzzy set, his study on Intuitionistic fuzzy and Type-2 fuzzy sets and systems overlaps with subjects such as Field.
His Fuzzy control system research incorporates elements of Defuzzification, Interpretability, Representation and Inference.
The concepts of his Interval study are interwoven with issues in Context, Type, Reduction, Structure and Statistics.
His study looks at the relationship between Type and topics such as Algorithm, which overlap with Centroid, Membership function, Fuzzy number and Rule-based system.
Between 2018 and 2021, his most popular works were:
- A Learning Automata-Based Multiobjective Hyper-Heuristic (24 citations)
- A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method (17 citations)
- A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum] (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Robert John mainly focuses on Fuzzy set, Fuzzy logic, Mathematical optimization, Fuzzy control system and Interval.
His work in the fields of Fuzzy set, such as Type-2 fuzzy sets and systems, intersects with other areas such as Related research.
His Fuzzy logic research includes themes of Feature, Data mining, Curse of dimensionality, Support vector machine and Cluster analysis.
When carried out as part of a general Mathematical optimization research project, his work on Evolutionary algorithm and Multi-objective optimization is frequently linked to work in Learning automata and Hyper-heuristic, therefore connecting diverse disciplines of study.
His work deals with themes such as Defuzzification, Interpretability, Representation and Inference, which intersect with Fuzzy control system.
His studies deal with areas such as Simulated annealing, Public transport, Type, Range and Key as well as Interval.
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