Degang Chen mostly deals with Rough set, Fuzzy set, Data mining, Fuzzy set operations and Fuzzy number. Degang Chen has researched Rough set in several fields, including Discrete mathematics, Algorithm, Reduction and Fuzzy logic. His Reduction research includes elements of Soft set, Point, Decision problem and Mathematical optimization.
His research investigates the connection with Data mining and areas like Artificial intelligence which intersect with concerns in Pattern recognition. His research in Fuzzy number focuses on subjects like Fuzzy classification, which are connected to Neuro-fuzzy, Kernel embedding of distributions and Variable kernel density estimation. His Defuzzification research integrates issues from Type-2 fuzzy sets and systems and Membership function.
His primary scientific interests are in Rough set, Data mining, Artificial intelligence, Fuzzy set and Fuzzy number. His research in Rough set intersects with topics in Discrete mathematics, Algorithm, Reduction and Fuzzy logic. His work deals with themes such as Entropy, Preprocessor, Data set and Knowledge representation and reasoning, which intersect with Data mining.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Pattern recognition. His Fuzzy set study frequently intersects with other fields, such as Mathematical optimization. His work carried out in the field of Fuzzy number brings together such families of science as Fuzzy set operations, Fuzzy classification and Membership function.
His primary areas of study are Rough set, Fuzzy logic, Computational intelligence, Artificial intelligence and Data mining. His research integrates issues of Algorithm, Reduction, Relation and Equivalence class in his study of Rough set. His Fuzzy rough sets and Fuzzy set investigations are all subjects of Fuzzy logic research.
His Computational intelligence study also includes fields such as
His primary areas of investigation include Rough set, Fuzzy logic, Feature selection, Artificial intelligence and Entropy. His Rough set study incorporates themes from Algorithm, Theoretical computer science and Equivalence relation. In the subject of general Fuzzy logic, his work in Fuzzy rough sets is often linked to Data modeling, thereby combining diverse domains of study.
His Feature selection research incorporates themes from Element, Data mining and Feature. Many of his studies on Data mining apply to Algorithm design as well. His Artificial intelligence study integrates concerns from other disciplines, such as Concept learning, Structure and Pattern recognition.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The parameterization reduction of soft sets and its applications
Degang Chen;E. C. C. Tsang;Daniel S. Yeung;Xizhao Wang.
Computers & Mathematics With Applications (2005)
On the generalization of fuzzy rough sets
D.S. Yeung;Degang Chen;E.C.C. Tsang;J.W.T. Lee.
IEEE Transactions on Fuzzy Systems (2005)
Attributes Reduction Using Fuzzy Rough Sets
E.C.C. Tsang;Degang Chen;D.S. Yeung;Xi-Zhao Wang.
IEEE Transactions on Fuzzy Systems (2008)
Feature selection in mixed data
Xiao Zhang;Changlin Mei;Degang Chen;Jinhai Li.
Pattern Recognition (2016)
Learning fuzzy rules from fuzzy samples based on rough set technique
Xizhao Wang;Eric C. C. Tsang;Suyun Zhao;Degang Chen.
Information Sciences (2007)
The Model of Fuzzy Variable Precision Rough Sets
Suyun Zhao;E. Tsang;Degang Chen.
IEEE Transactions on Fuzzy Systems (2009)
Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications
Qinghua Hu;Lei Zhang;Degang Chen;Witold Pedrycz.
International Journal of Approximate Reasoning (2010)
Rough set theory for the interval-valued fuzzy information systems
Zengtai Gong;Bingzhen Sun;Degang Chen.
Information Sciences (2008)
Fuzzy rough set theory for the interval-valued fuzzy information systems
Bingzhen Sun;Zengtai Gong;Degang Chen.
Information Sciences (2008)
A Fitting Model for Feature Selection With Fuzzy Rough Sets
Changzhong Wang;Yali Qi;Mingwen Shao;Qinghua Hu.
IEEE Transactions on Fuzzy Systems (2017)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: