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We describe in this book, new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. In this book, we are extending the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each te- nique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in real-world applications. We c- sider in particular the problems of face, fingerprint and voice recognition. We also consider the problem of recognizing a person by integrating the information given by the face, fingerprint and voice of the person. Other types of applications solved with type-2 fuzzy logic and SC techniques, include intelligent control, intelligent manuf- turing, and adaptive noise cancellation. This book is intended to be a major reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation.
Über den Autor / die Autorin
Patricia Melin holds the Doctor in Science degree (Doctor Habilitatus D.Sc.) in Computer Science from the Polish Academy of Sciences. She 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 head of the research group on Hybrid Neural Intelligent Systems (2000-present). 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 Journal of Information Sciences and IEEE Transactions on Fuzzy Systems. She is member of NAFIPS, IFSA, and IEEE. She belongs to the Mexican Research System with level III. 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 published over 300 journal papers, 20 authored books, 50 edited books, and more than 300 papers in conference proceedings, for a total of more than 800 publications with h-index of 86 in Google Scholar. She is Editor-in-Chief of the Advances in Fuzzy Systems journal (Wiley). 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, JAMRIS, Fuzzy Sets and Systems. She 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.
Martha Ram¿rez holds the B.S. in Computer Science, M.S. in Computer Science, and the Ph.D. in Computer Science from Tijuana Institute of Technology. Currently she works at Tecnologico Nacional de Mexico in Mexico City. Her current research interests include hybrid intelligent systems, neural networks and fuzzy systems. She has published more 10 papers in time series prediction, classification and clustering using supervised and unsupervised neural network models, in addition to type-1 and type-2 fuzzy logic for aggregation of responses in ensembles and modular neural networks.
Oscar Castillo 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 and 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 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, 20 authored books, 100 edited books, 300 papers in conference proceedings, and more than 300 chapters in edited books, in total more than 1180 publications (according to Scopus) with h index of 97 and more than 31000 citations according to 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, Soft Computing, Non-Linear Studies, Fuzzy Sets and Systems, JAMRIS and Engineering Letters. He is currently Associate
Zusammenfassung
We describe in this book, new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. In this book, we are extending the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each te- nique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in real-world applications. We c- sider in particular the problems of face, fingerprint and voice recognition. We also consider the problem of recognizing a person by integrating the information given by the face, fingerprint and voice of the person. Other types of applications solved with type-2 fuzzy logic and SC techniques, include intelligent control, intelligent manuf- turing, and adaptive noise cancellation. This book is intended to be a major reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation.
Zusatztext
From the reviews:
“This research monograph offers a broad coverage of the recent developments in … type-2 fuzzy sets and fuzzy systems. … The monograph is arranged into 17 concise and well-focused chapters covering a wealth of applications and methodologies of type-2 fuzzy sets. … chapters brings some useful motivating notes and elaborates on the algorithms pertinent to the problem at hand. … a timely compendium of applications of type-2 fuzzy systems and offers the reader a sound overview of design techniques supporting the construction of such architectures.” (Witold Pedrycz, Zentralblatt MATH, Vol. 1171, 2009)
Bericht
From the reviews:
"This research monograph offers a broad coverage of the recent developments in ... type-2 fuzzy sets and fuzzy systems. ... The monograph is arranged into 17 concise and well-focused chapters covering a wealth of applications and methodologies of type-2 fuzzy sets. ... chapters brings some useful motivating notes and elaborates on the algorithms pertinent to the problem at hand. ... a timely compendium of applications of type-2 fuzzy systems and offers the reader a sound overview of design techniques supporting the construction of such architectures." (Witold Pedrycz, Zentralblatt MATH, Vol. 1171, 2009)
