What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
Guiwu Wei spends much of his time researching Multiple attribute, Fuzzy logic, Operator, Mathematical optimization and Fuzzy set operations.
Multiple attribute is a subfield of Artificial intelligence that Guiwu Wei tackles.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition.
In his study, Type, Generalized mean, Maclaurin symmetric mean and Calculus is inextricably linked to Aggregate, which falls within the broad field of Fuzzy logic.
In Mathematical optimization, Guiwu Wei works on issues like Rank, which are connected to Correlation coefficient.
The Fuzzy set operations study combines topics in areas such as Fuzzy number and Fuzzy classification.
His most cited work include:
- Some induced geometric aggregation operators with intuitionistic fuzzy information and their application to group decision making (535 citations)
- Hesitant fuzzy prioritized operators and their application to multiple attribute decision making (425 citations)
- GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting (337 citations)
What are the main themes of his work throughout his whole career to date?
Multiple attribute, Fuzzy logic, Artificial intelligence, Operator and Group decision-making are his primary areas of study.
His study in Multiple attribute is interdisciplinary in nature, drawing from both Pythagorean theorem, Tuple, Theoretical computer science, Ideal and Interval valued.
Guiwu Wei interconnects Mathematical optimization and Data mining in the investigation of issues within Fuzzy logic.
His Data mining research is multidisciplinary, incorporating elements of Ranking and Grey relational analysis.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Natural language processing.
Guiwu Wei focuses mostly in the field of Fuzzy number, narrowing it down to topics relating to Fuzzy set operations and, in certain cases, Fuzzy classification.
He most often published in these fields:
- Multiple attribute (55.80%)
- Fuzzy logic (46.74%)
- Artificial intelligence (34.78%)
What were the highlights of his more recent work (between 2019-2021)?
- Group decision-making (26.81%)
- Multiple attribute (55.80%)
- Artificial intelligence (34.78%)
In recent papers he was focusing on the following fields of study:
Guiwu Wei mostly deals with Group decision-making, Multiple attribute, Artificial intelligence, Fuzzy logic and Tuple.
While working in this field, Guiwu Wei studies both Multiple attribute and EDAS.
His biological study spans a wide range of topics, including Machine learning and Natural language processing.
Guiwu Wei combines subjects such as Pythagorean theorem and Entropy with his study of Fuzzy logic.
His studies in Tuple integrate themes in fields like Theoretical computer science, Selection, Dual and Rule-based machine translation.
In his work, Extension is strongly intertwined with Mathematical optimization, which is a subfield of Fuzzy set.
Between 2019 and 2021, his most popular works were:
- VIKOR Method for MAGDM Based on Q-Rung Interval-Valued Orthopair Fuzzy Information and Its Application to Supplier Selection of Medical Consumption Products. (35 citations)
- TOPSIS Method for Developing Supplier Selection with Probabilistic Linguistic Information (33 citations)
- Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations (28 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
The scientist’s investigation covers issues in Group decision-making, Multiple attribute, Artificial intelligence, Probabilistic logic and Fuzzy logic.
Tuple and Operations research are fields of study that intersect with his Group decision-making research.
As part of his studies on Multiple attribute, Guiwu Wei often connects relevant subjects like Natural language processing.
His Probabilistic logic research includes themes of Machine learning, Computational intelligence, Rule-based machine translation and Location planning.
His work in the fields of Fuzzy logic, such as Fuzzy set and Pythagorean fuzzy sets, intersects with other areas such as Generalization.
His Pythagorean fuzzy sets research includes elements of Pythagorean theorem and Entropy.
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