UID:
almahu_9948689690702882
Format:
XXI, 173 p. 56 illus., 50 illus. in color.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030722807
Series Statement:
Studies in Fuzziness and Soft Computing, 408
Content:
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.
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030722791
Additional Edition:
Printed edition: ISBN 9783030722814
Additional Edition:
Printed edition: ISBN 9783030722821
Language:
English
DOI:
10.1007/978-3-030-72280-7
URL:
https://doi.org/10.1007/978-3-030-72280-7
