Design of Interpretable Fuzzy Systems (Record no. 80195)
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000 -LEADER | |
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fixed length control field | 03556nam a22005175i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-52881-6 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20220801221919.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 170202s2017 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319528816 |
-- | 978-3-319-52881-6 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.3 |
100 1# - AUTHOR NAME | |
Author | Cpałka, Krzysztof. |
245 10 - TITLE STATEMENT | |
Title | Design of Interpretable Fuzzy Systems |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2017. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XI, 196 p. 65 illus. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Computational Intelligence, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-52881-6 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2017. |
336 ## - | |
-- | text |
-- | txt |
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-- | computer |
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-- | rdamedia |
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-- | online resource |
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347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 1860-9503 ; |
912 ## - | |
-- | ZDB-2-ENG |
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-- | ZDB-2-SXE |
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