What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
His primary areas of investigation include Fuzzy set, Artificial intelligence, Fuzzy logic, Fuzzy set operations and Fuzzy classification.
His research in Fuzzy set intersects with topics in Discrete mathematics, Algorithm, Theoretical computer science and Mathematical optimization.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Expected value, Decision theory, Operator and Ordered weighted averaging aggregation operator.
Ronald R. Yager has included themes like Machine learning and Natural language processing in his Artificial intelligence study.
His Fuzzy logic research integrates issues from Structure, Inference and Information retrieval.
His work in Fuzzy set operations addresses issues such as Defuzzification, which are connected to fields such as Membership function and Fuzzy associative matrix.
His most cited work include:
- On ordered weighted averaging aggregation operators in multicriteria decisionmaking (5681 citations)
- Essentials of Fuzzy Modeling and Control (1540 citations)
- Some geometric aggregation operators based on intuitionistic fuzzy sets (1441 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Fuzzy set, Fuzzy logic, Fuzzy set operations and Fuzzy number.
The study of Artificial intelligence is intertwined with the study of Machine learning in a number of ways.
In his work, Algebra is strongly intertwined with Discrete mathematics, which is a subfield of Fuzzy set.
His study in Fuzzy logic is interdisciplinary in nature, drawing from both Algorithm, Mathematical optimization and Data mining.
His work is dedicated to discovering how Mathematical optimization, Operator are connected with Ordered weighted averaging aggregation operator and other disciplines.
Ronald R. Yager combines subjects such as Defuzzification and Fuzzy classification with his study of Fuzzy set operations.
He most often published in these fields:
- Artificial intelligence (36.20%)
- Fuzzy set (32.11%)
- Fuzzy logic (31.37%)
What were the highlights of his more recent work (between 2013-2021)?
- Fuzzy logic (31.37%)
- Artificial intelligence (36.20%)
- Fuzzy set (32.11%)
In recent papers he was focusing on the following fields of study:
Ronald R. Yager mainly investigates Fuzzy logic, Artificial intelligence, Fuzzy set, Mathematical optimization and Measure.
His Fuzzy logic research incorporates themes from Rough set, Multiple-criteria decision analysis, Simple, Construct and Interval.
His Artificial intelligence study integrates concerns from other disciplines, such as Natural language processing, Machine learning and Pattern recognition.
His research integrates issues of Discrete mathematics, Theoretical computer science and Data science in his study of Fuzzy set.
His Mathematical optimization study incorporates themes from Operator, Fuzzy measure theory, Set, Choquet integral and Measure.
His Measure study also includes fields such as
- Belief structure and related Dempster–Shafer theory,
- Probability distribution and related Entropy,
- Probabilistic logic which is related to area like Data mining.
Between 2013 and 2021, his most popular works were:
- Pythagorean membership grades in multicriteria decision making (769 citations)
- Generalized Orthopair Fuzzy Sets (334 citations)
- Deep learning approach for active classification of electrocardiogram signals (298 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
Ronald R. Yager spends much of his time researching Artificial intelligence, Mathematical optimization, Fuzzy set, Fuzzy logic and Probability distribution.
The study incorporates disciplines such as Machine learning, Pattern recognition and Imprecise probability in addition to Artificial intelligence.
His studies deal with areas such as Operator, Measure, Fuzzy measure theory, Set and Choquet integral as well as Mathematical optimization.
His Fuzzy set research focuses on Discrete mathematics and how it connects with Algebra and Interval valued.
His Fuzzy control system study, which is part of a larger body of work in Fuzzy logic, is frequently linked to Bibliometric analysis, bridging the gap between disciplines.
His biological study spans a wide range of topics, including Defuzzification and Fuzzy classification.
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