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

József Dombi, Orsolya Csiszár (Autoren)

Buch | Hardcover

XXI, 173 Seiten

2021
Springer International Publishing (Verlag)
978-3-030-72279-1 (ISBN)

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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.

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.

Erscheinungsdatum	30.04.2021
Reihe/Serie	Studies in Fuzziness and Soft Computing
Zusatzinfo	XXI, 173 p. 56 illus., 50 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	419 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Technik
Schlagworte	Computational Intelligence • Explainable Neural Networks • Fuzzy Logic • Multi-criteria Decision tools • Neural networks
ISBN-10	3-030-72279-1 / 3030722791
ISBN-13	978-3-030-72279-1 / 9783030722791
Zustand	Neuware