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

1. Auflage 2021
ISBN: 978-3-030-72282-1
Verlag: Springer International Publishing

Buch, Englisch, Band 408, 173 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 306 g

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.

Csiszár, Orsolya

Dombi, József

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Berechenbarkeitstheorie, Komplexitätstheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

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.