What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Algebra
His scientific interests lie mostly in Rough set, Fuzzy set, Fuzzy logic, Artificial intelligence and Type-2 fuzzy sets and systems.
His Rough set research is under the purview of Data mining.
His work on Fuzzy set operations and Fuzzy number is typically connected to Information processing as part of general Fuzzy set study, connecting several disciplines of science.
His Fuzzy set operations research is multidisciplinary, incorporating elements of Discrete mathematics, Equivalence relation, Defuzzification and Fuzzy classification.
His study in Fuzzy logic is interdisciplinary in nature, drawing from both Pure mathematics, Intuitionistic logic, Entropy and Knowledge base.
Chris Cornelis has researched Artificial intelligence in several fields, including Mathematical economics, Machine learning and Pattern recognition.
His most cited work include:
- On the representation of intuitionistic fuzzy t-norms and t-conorms (437 citations)
- Implication in intuitionistic fuzzy and interval-valued fuzzy set theory: construction, classification, application (349 citations)
- Attribute selection with fuzzy decision reducts (172 citations)
What are the main themes of his work throughout his whole career to date?
Chris Cornelis mainly focuses on Artificial intelligence, Fuzzy logic, Rough set, Fuzzy set and Data mining.
The study incorporates disciplines such as Natural language processing, Machine learning and Pattern recognition in addition to Artificial intelligence.
His biological study spans a wide range of topics, including Discrete mathematics, Contrast and Pure mathematics.
His research in Fuzzy set intersects with topics in Representation, Theoretical computer science and Fuzzy control system.
As a member of one scientific family, Chris Cornelis mostly works in the field of Data mining, focusing on k-nearest neighbors algorithm and, on occasion, Reduction.
His Fuzzy set operations study incorporates themes from Fuzzy number, Defuzzification and Fuzzy classification.
He most often published in these fields:
- Artificial intelligence (47.35%)
- Fuzzy logic (40.71%)
- Rough set (30.97%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (47.35%)
- Rough set (30.97%)
- Data mining (30.53%)
In recent papers he was focusing on the following fields of study:
Chris Cornelis focuses on Artificial intelligence, Rough set, Data mining, Fuzzy logic and Machine learning.
His Artificial intelligence study frequently draws connections to other fields, such as Pattern recognition.
The Rough set study combines topics in areas such as Discrete mathematics, Fuzzy set, Approximation operators and Algorithm.
Chris Cornelis works in the field of Fuzzy set, namely Fuzzy set operations.
His work carried out in the field of Fuzzy set operations brings together such families of science as Fuzzy number, Fuzzy classification, Robustness and Complete information.
Chris Cornelis interconnects Representation, Weighted arithmetic mean and Extension in the investigation of issues within Fuzzy logic.
Between 2014 and 2021, his most popular works were:
- Neighborhood operators for covering-based rough sets (67 citations)
- Fuzzy neighborhood operators based on fuzzy coverings (58 citations)
- IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification (56 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Algebra
Chris Cornelis mostly deals with Artificial intelligence, Rough set, Data mining, Dominance-based rough set approach and Fuzzy set operations.
His Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Rough set research incorporates elements of Discrete mathematics, Spectral theorem, Partition and Decision rule.
His Data mining research integrates issues from Class and Fuzzy logic.
His Dominance-based rough set approach research incorporates themes from Approximations of π, Theoretical computer science, Boolean algebra and Complete information.
His research integrates issues of Fuzzy number and Fuzzy classification in his study of Fuzzy set operations.
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