Type-2 fuzzy sets and systems are paradigms which seek to realize computationally efficient fuzzy systems with the ability to give excellent performance in the face of highly uncertain conditions.
Specifically, type-2 fuzzy sets provide a framework for the comprehensive capturing and modelling of uncertain data, which, together with approaches such as clustering and similarity measures (to name but two) provides strong capability for reasoning about and with uncertain information sources in a variety of contexts and applications.
Type-2 fuzzy systems combine the potential of type-2 fuzzy sets with the strengths of rule-based inference in order to provide highly capable inference systems over uncertain data which remain white-box systems (i.e. interpretable).
The aim of this special session is to present and focus top quality research in the areas related to the practical aspects and applications of type-2 fuzzy sets and systems. The session will also provide a forum for the academic community and industry to report on recent advances within the type-2 fuzzy sets and systems research. Topics include, but are not limited to:
Type-2 Applications
Applications including similarity and distance measures for type-2 fuzzy sets
Data analysis*
Robotics*
Decision Making*
Clustering and Classification*
Modelling*
Computing with words*
Type-2 Fuzzy Agents
Any other application area that employs type-2 fuzzy sets
* using type-2 fuzzy sets and/or fuzzy systems
Important Dates:
University of Nottingham
Huazhong University of Science (HUST)
University of Essex
Technical Committee:
§ Prof. Sabrina Senatori, University of Salerno, Italy
§ Prof. Giovanni Acampora, University of Naples Federico II, Italy
§ Prof. Jose Sanz, Universidad Publica de Navarra, Spain
§ Prof. Chang-Shing Lee, National University of Tainan, Taiwan
§ Prof. Mahdi Mahfouf, University of Sheffield, United Kingdom