Dombi / Csiszár Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

Erscheinungsjahr 2021
ISBN: 978-3-030-72280-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 408, 173 Seiten, eBook

Reihe: Studies in Fuzziness and Soft Computing

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.

Zielgruppe

Research

Autoren/Hrsg.

Dombi, József

Csiszár, Orsolya

Inhaltsverzeichnis

Chapter 1: Connectives: Conjunctions, Disjunctions and Negations.- Chapter 2: Implications.- Chapter 3: Equivalences.- Chapter 4: Modi?ers and Membership Functions in Fuzzy Sets.- Chapter 5: Aggregative Operators.- Chapter 6:  Preference Operators.