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

József Dombi|Orsolya Csiszár

ISBN 10: 3030722791 / ISBN 13: 9783030722791

Verlag: Springer International Publishing, 2021

Beschreibung

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the current state-of-the-art in Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision ToolsPresents recent research focusing on a special class&nbspof continuous-valued logic and multi-criteria decision tools.

Bestandsnummer des Verkäufers 458553505

Bibliografische Details

• Titel: Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools
• Verlag: Springer International Publishing
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 3030722791
• ISBN-13: 9783030722791
• Einband: Gebunden
• Zustand: New
• Verkäuferkataloge:
  • Mathematik/Naturwissenschaften/Technik/Medizin

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.