Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools (Studies in Fuzziness and Soft Computing, 408)

Dombi, József, Csiszár, Orsolya

ISBN 10: 3030722791 / ISBN 13: 9783030722791

Verlag: Springer, 2021

Beschreibung

New.

Bestandsnummer des Verkäufers D8F0-0-M-3030722791-6

Bibliografische Details

• Titel: Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools (Studies in Fuzziness and Soft Computing, 408)
• Verlag: Springer
• Veröffentlichungsdatum: 2021
• Sprache: Englisch
• ISBN-10: 3030722791
• ISBN-13: 9783030722791
• Bindung: Hardcover
• Zustand: New
• Buchtyp: book

Über diesen Titel

Inhaltsangabe

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable - and even, in many cases, more efficient. 

Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.

Von der hinteren Coverseite

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable and even, in many cases, more efficient. 

Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.