Fuzzy Evidence in Identification, Forecasting and Diagnosis: 275 - Rilegato

Rotshtein, Alexander P.; Rakytyanska, Hanna B.

Rilegato

ISBN 10: 3642257852 ISBN 13: 9783642257858

Casa editrice: Springer-Nature New York Inc, 2012

Riassunto

The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving.

The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fuzzy relations and fuzzy rules. Chapter 8 presents a method for extracting fuzzy relations from data. All the algorithms presented in Chapters 2-8 are validated by computer experiments and illustrated by solving medical and technical forecasting and diagnosis problems. Finally, Chapter 9 includes applications of the proposed methodology in dynamic and inventory control systems, prediction of results of football games, decision making in road accident investigations, project management and reliability analysis.

Su questo libro

L'autore:

Professor Yogesan is the Research Director of the Australian e-Health Research Centre and a Senior Research Fellow of the National Health and Medical Research Council in Australia. He has worked at Stanford University Eye Institute as a Senior Fulbright Scholar in 2011. He is the President of the Australasian Telehealth Society and a Board of Directors of the International Society for Telemedicine and E-Health. He has obtained many awards including one of the Inventors of the year awards in 2006 and 2008 (for Eye Scan device and i-Test). He was selected as WA's top medical and health researcher in 2002, nominated for citizen of the year in 2007 and Local champion of 2007 in Perth. He has published over 85 peer-reviewed research papers and books in the field, including the first text book on Teleophthalmology (with Springer). He has strong record in translation of research findings into clinical practice and holds patent portfolio of more than 30 applications in the field.  Professor Goldschmidt is a leading ophthalmologist and a pioneer in the field of medical informatics in USA. He is the Medical Director at the US Department of Veterans Affairs (VA) in Palo Alto, CA. He is also a clinical professor in ophthalmology at the Stanford School of Medicine. Professor Goldschmidt is the Director for the world famous national teleretinal screening program at VA. He is a pioneer in introducing telemedicine and an electronic patient record system at the VA, which is the largest system successfully functioning in the US with 6 million patient’s records. His work is becoming increasingly recognized at the forefront in this developing field internationally. Professor Cuadros is an optometrist from the School of Optometry at the University of California, Berkeley. He is the pioneer in introducing eye screening program in California especially in the underserved communities. He himself reads retinal photos for diabetic retinopathy. He has established screening standards and trains screeners for diabetic retinopathy. He is rolling out many remote screening centers in central California in collaboration with the California Healthcare Foundation.

Contenuti:

Preface.- Fundamentals of intellectual technologies.- Direct inference based on fuzzy rules.- Fuzzy rules tuning for direct inference.- Fuzzy rules extraction from experimental data.- Inverse inference based on fuzzy relational equations.- Inverse inference with fuzzy relations tuning.- Inverse inference based on fuzzy rules.- Fuzzy relations extraction from experimental data.- Applied fuzzy systems.

Su questa edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2012
• ISBN 10: 3642257852
• ISBN 13: 9783642257858
• Rilegatura: Copertina rigida
• Numero di pagine: 313