
Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools: 408 1st ed. 2021 Edition
Author(s): József Dombi (Author), Orsolya Csiszár (Author)
- Publisher: Springer
- Publication Date: 29 April 2022
- Edition: 1st ed. 2021
- Language: English
- Print length: 194 pages
- ISBN-10: 3030722821
- ISBN-13: 9783030722821
Book Description
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.
Editorial Reviews
From the Back Cover
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.
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