Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools
(Sprache: Englisch)
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...
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Klappentext zu „Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools “
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.Inhaltsverzeichnis zu „Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools “
Chapter 1: Connectives: Conjunctions, Disjunctions and Negations.- Chapter 2: Implications.- Chapter 3: Equivalences.- Chapter 4: Modifiers and Membership Functions in Fuzzy Sets.- Chapter 5: Aggregative Operators.- Chapter 6: Preference Operators.
Bibliographische Angaben
- Autoren: József Dombi , Orsolya Csiszár
- 2021, 1st ed. 2021, XXI, 173 Seiten, 50 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3030722791
- ISBN-13: 9783030722791
Sprache:
Englisch
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