The third edition of this textbook presents a further updated approach
to fuzzy sets and systems that can model uncertainty — i.e.,
“type-2” fuzzy sets and systems. The author demonstrates how to
overcome the limitations of classical fuzzy sets and systems, enabling
a wide range of applications, from time-series forecasting to
knowledge mining to classification to control and to explainable AI
(XAI). This latest edition again begins by introducing classical
(type-1) fuzzy sets and systems, and then explains how they can be
modified to handle uncertainty, leading to type-2 fuzzy sets and
systems. New material is included about how to obtain fuzzy set word
models that are needed for XAI, similarity of fuzzy sets, a
quantitative methodology that lets one explain in a simple way why the
different kinds of fuzzy systems have the potential for performance
improvements over each other, and new parameterizations of membership
functions that have the potential for achieving even greater
performance for all kinds of fuzzy systems. For hands-on experience,
the book provides information on accessing MATLAB, Java, and Python
software to complement the content. The book features a full suite of
classroom material.
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Produktdetaljer
ISBN
9783031353789
Publisert
2024
Utgave
3. utgave
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter