2020 Fuzz-IEEE part of WCCI 2020
Glasgow, Scotland, UK July 19-24, 2020, Fuzz’2020
Special Session: Trends and developments on Type-2 Fuzzy Sets and Systems
Dr. Oscar Castillo, Tijuana Institute Technology , Tijuana Mexico
Dr. Pranab Kumar Muhuri, South Asian University, New Delhi-India
Dr. Patricia Melin, Tijuana Institute of Technology Tijuana, Mexico
Dr. Amit K. Shukla, Post-Doc Fellow at ENSSAT, IRISA Lab, Univ. of Rennes , Lannion, France
Initially proposed by Zadeh in 1975, higher order fuzzy sets (or type-m fuzzy sets) actually gained interest of research community in last 20 years. It has evolved from an emerging field to full-fledged research area where researchers have proved its significance in various real-world applications such as: time series, real-time systems, aeronautics, gene expression analysis etc. Mostly, type-2 fuzzy sets (T2 FSs) or interval T2 FSs (IT2 FSs) has been used in these applications only because they potentially hold more implication than the traditional FSs (or type-1 FSs). The membership function modelling in these T2 FSs and IT2 FSs offers more degree of freedom as compared to the type-1 FSs. Technically, the membership function uncertainty is uniformly weighted in the IT2 FSs, while it is non-uniform in T2 FSs. According to the widely used indexing platform, Scopus, there are already more than 4,500 publications on T2 FSs till the mid of 2019 and the number of publications is increasing rapidly every month. One of the pioneer in this field, Prof. Jerry. M. Mendel, recently established that a general T2 fuzzy logic systems (GT2 FLS) has the capability to give better (or at least equal) performance than a IT2 FLS which on the other hand have the potential to produce better (or at least equal) performance than a T1 FLS. This has led a number of researchers (but very few) to focus on this GT2 FSs. The modelling and representation has now been well established in the literature for the researchers so that it can be explored for various applications. This warrants more and more research attention from the scientific community on this important topic, especially since everyday newer and newer systems are emerging across all the domains of science and engineering, e.g. social networks, big data analytics, cyber security, cyber-physical systems, cloud computing etc. Moreover, uncertainty modelling using T2 FSs has a lot of potential within the framework of machine learning and deep learning.
Scope and Topics
This special session aims to introduce cutting edge research concepts on T2 FSs and Systems and their applications in a number of emerging systems
Topics of interest (not limited to)
Type-2 fuzzy sets for uncertainty handling in Cyber-Physical Systems/ Internet of Things
Type-2 fuzzy sets for Cloud Computing / Big Data Analytics /
Type-2 fuzzy sets for Smart Transportation Systems
Type-2 fuzzy sets for Social Network Analysis
Type-2 fuzzy sets and systems for Cyber Security
Type-2 fuzzy sets for Secure Communication
Type-2 fuzzy sets in Multimedia Applications
Type-2 fuzzy sets in Computing with words
Type-2 fuzzy sets for Image Processing
Type-2 fuzzy sets in Evolutionary Optimization
Type-2 fuzzy sets and systems in Machine learning / Deep learning framework
Type-2 fuzzy sets for Power Systems / Energy Optimization / Green Computing
Type-2 fuzzy sets based uncertainty modelling Vehicle Routing Problem
Type-2 fuzzy sets for financial data management and decision making
Any other application areas with T2 FS based uncertainty modelling
Oscar Castillo (email@example.com) holds the Doctor in Science degree (Doctor Habilitatus) in Computer Science from the Polish Academy of Sciences (with the Dissertation “Soft Computing and Fractal Theory for Intelligent Manufacturing”). He is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico. In addition, he is serving as Research Director of Computer Science and head of the research group on Hybrid Fuzzy Intelligent Systems. Currently, he is President of HAFSA (Hispanic American Fuzzy Systems Association) and Past President of IFSA (International Fuzzy Systems Association). Prof. Castillo is also Chair of the Mexican Chapter of the Computational Intelligence Society (IEEE). He also belongs to the Technical Committee on Fuzzy Systems of IEEE and to the Task Force on “Extensions to Type-1 Fuzzy Systems”. He is also a member of NAFIPS, IFSA and IEEE. He belongs to the Mexican Research System (SNI Level 3). His research interests are in Type-2 Fuzzy Logic, Fuzzy Control, Neuro-Fuzzy and Genetic-Fuzzy hybrid approaches. He has published over 300 journal papers, 10 authored books, 40 edited books, 200 papers in conference proceedings, and more than 300 chapters in edited books, in total more than 850 publications according to Scopus (H index=58), and more than 900 publications according to Research Gate (H index=71 in Google Scholar). He has been Guest Editor of several successful Special Issues in the past, like in the following journals: Applied Soft Computing, Intelligent Systems, Information Sciences, Non-Linear Studies, Fuzzy Sets and Systems, JAMRIS and Engineering Letters. He is currently Associate Editor of the Information Sciences Journal, Applied Soft Computing Journal, Granular Computing Journal and the International Journal on Fuzzy Systems. Finally, he has been elected IFSA Fellow in 2015 and MICAI Fellow member in 2017. He has been recognized as Highly Cited Researcher in 2017 and 2018 by Clarivate Analytics because of having multiple highly cited papers in Web of Science (in the best 1% of Computer Science in the World).
Pranab K. Muhuri (firstname.lastname@example.org) received his Ph.D. degree in Computer Engineering in 2005 from IT-BHU [now Indian Institute of Technology, (BHU)], Varanasi, India. He is a Professor with the Department of Computer Science, South Asian University, India, and leading the computational intelligence research group. Pranab has been in the editorial board /guest editor and/or in the reviewers’ panel of a number of reputed journals such as Applied Soft Computing, Granular Computing, IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Computers and Industrial Engineering, Engineering Applications of Artificial Intelligence, International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems, Wireless Personal Communication etc. He is serving in the Editorial Boards of two journals: Applied Soft Computing, and Engineering Application of Artificial Intelligence.
Patricia Melin (email@example.com) is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico, since 1998. In addition, she is serving as Director of Graduate Studies in Computer Science and is head of the research group on Hybrid Neural Intelligent Systems (2000-present). She holds the Doctor in Science degree (Doctor Habilitatus D.Sc.) in Computer Science from the Polish Academy of Sciences. Prof. Melin has published nearly 700 publications in indexed journals, book chapters, and conference proceedings, as well as nearly 50 books, and as consequence of this she has achieved more than 14000 citations with an H index of 64 in Google Scholar. In addition, she has been awarded the Highly Cited Researcher recognition in the area of Computer Science in 2017 and 2018 by Clarivate Analytics because she is in the top 1% cited author in this area. She has also been advisor of more than 80 graduate students in computer science at the Ph.D. and masters levels. She is past President of NAFIPS (North American Fuzzy Information Processing Society) 2019-2020. Prof. Melin is the founding Chair of the Mexican Chapter of the IEEE Computational Intelligence Society. She is member of the IEEE Neural Network Technical Committee (2007 to present), the IEEE Fuzzy System Technical Committee (2014 to present) and is Chair of the Task Force on Hybrid Intelligent Systems (2007 to present) and she is currently Associate Editor of the Information Sciences Journal, IEEE Transactions on Fuzzy Systems and Journal of Complex and Intelligent Systems. She is member of NAFIPS, IFSA, and IEEE. She belongs to the Mexican Research System with level III (highest level). Her research interests are in Modular Neural Networks, Type-2 Fuzzy Logic, Pattern Recognition, Fuzzy Control, Neuro-Fuzzy and Genetic-Fuzzy hybrid approaches. She has served as Guest Editor of several Special Issues in the past, in journals like: Applied Soft Computing, Intelligent Systems, Information Sciences, Non-Linear Studies, Engineering Applications of Artificial Intelligence, Fuzzy Sets and Systems.
Dr. Amit K. Shukla (firstname.lastname@example.org)is currently a Post-Doctoral Fellow at ENSSAT, IRISA LAB, France. He received his Ph.D. in Computer Science from South Asian University, New Delhi, India. He is a gold medal holder in his master’s degree (2013) in Computer Science from South Asian University. He has chaired the ACM chapter of South Asian University from 2011-12. He is also an IEEE Young Professional and an active member of societies such as: IEEE Computational Intelligence Society and EUSFLAT. His research areas include: higher order uncertainty modeling, fuzzy sets and systems, anomaly detection, real-time systems, deep learning, and soft-computing techniques.