Design of interpretable fuzzy systems

This book shows that the term "interpretability" goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve th...

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Bibliographic Details
Main Author: Cpałka, Krzysztof, (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2017.
Series: Studies in computational intelligence ; v. 684.
Subjects:
Fuzzy systems.
Fuzzy logic.
Fuzzy sets.
elektronické knihy
electronic books
ISBN: 9783319528816
9783319528809
Physical Description: 1 online resource (xi, 196 pages) : illustrations

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100 1 |a Cpałka, Krzysztof,  |e author. 
245 1 0 |a Design of interpretable fuzzy systems /  |c Krzysztof Cpałka. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (xi, 196 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Studies in computational intelligence,  |x 1860-949X ;  |v volume 684 
504 |a Includes bibliographical references and index. 
505 0 |a Preface -- Acknowledgements -- Chapter1: Introduction -- Chapter2: Selected topics in fuzzy systems designing -- Chapter3: Introduction to fuzzy system interpretability -- Chapter4: Improving fuzzy systems interpretability by appropriate selection of their structure -- Chapter5: Interpretability of fuzzy systems designed in the process of gradient learning -- Chapter6: Interpretability of fuzzy systems designed in the process of evolutionary learning -- Chapter7: Case study: interpretability of fuzzy systems applied to nonlinear modelling and control -- Chapter8: Case study: interpretability of fuzzy systems applied to identity verification -- Chapter9: Concluding remarks and future perspectives -- Index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book shows that the term "interpretability" goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Fuzzy systems. 
650 0 |a Fuzzy logic. 
650 0 |a Fuzzy sets. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Printed edition:  |z 9783319528809 
830 0 |a Studies in computational intelligence ;  |v v. 684.  |x 1860-949X 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-52881-6  |y Plný text 
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993 |x NEPOSILAT  |y EIZ 

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